Concatenating data objects in a vast data storage network

ABSTRACT

A method includes identifying an independent data object of a plurality of independent data objects for retrieval from dispersed storage network (DSN) memory. The method further includes determining a mapping of the plurality of independent data objects into a data matrix, wherein the mapping is in accordance with the dispersed storage error encoding function. The method further includes identifying, based on the mapping, an encoded data slice of the set of encoded data slices corresponding to the independent data object. The method further includes sending a retrieval request to a storage unit of the DSN memory regarding the encoded data slice. When the encoded data slice is received, the method further includes decoding the encoding data slice in accordance with the dispersed storage error encoding function and the mapping to reproduce the independent data object.

CROSS REFERENCE TO RELATED PATENTS

The present U.S. Utility Patent Application claims priority pursuant to35 U.S.C. § 120 as a continuation of U.S. Utility application Ser. No.16/988,247, entitled “Concatenating Data Objects For Storage In A VastData Storage Network”, filed Aug. 7, 2020, which is a continuation ofU.S. Utility application Ser. No. 16/171,794, entitled “ConcatenatingData Objects for Storage in a Dispersed Storage Network”, filed Oct. 26,2018, issued as U.S. Pat. No. 10,776,204 on Sep. 15, 2020, which is acontinuation of U.S. Utility application Ser. No. 15/679,569, entitled“Concatenating Data Objects for Storage in a Dispersed Storage Network”,filed Aug. 17, 2017, issued as U.S. Pat. No. 10,169,150 on Jan. 1, 2019,which is a continuation of U.S. Utility application Ser. No. 15/351,628,entitled “Concatenating Data Objects for Storage in a Dispersed StorageNetwork”, filed Nov. 15, 2016, issued as U.S. Pat. No. 9,798,619 on Oct.24, 2017, which is a continuation of U.S. Utility application Ser. No.14/589,391, entitled “Concatenating Data Objects for Storage in aDispersed Storage Network”, filed Jan. 5, 2015, issued as U.S. Pat. No.9,529,834 on Dec. 27, 2016, which claims priority pursuant to 35 U.S.C.§ 119(e) to U.S. Provisional Application No. 61/944,742, entitled“Executing Tasks in a Distributed Storage and Task Network”, filed Feb.26, 2014, all of which are hereby incorporated herein by reference intheir entirety and made part of the present U.S. Utility PatentApplication for all purposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not applicable.

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not applicable.

BACKGROUND OF THE INVENTION Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersed storage of data and distributed taskprocessing of data.

Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc., on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system in accordance with the present invention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a diagram of an example of a distributed storage and taskprocessing in accordance with the present invention;

FIG. 4 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing in accordance with thepresent invention;

FIG. 5 is a logic diagram of an example of a method for outbound DSTprocessing in accordance with the present invention;

FIG. 6 is a schematic block diagram of an embodiment of a dispersederror encoding in accordance with the present invention;

FIG. 7 is a diagram of an example of a segment processing of thedispersed error encoding in accordance with the present invention;

FIG. 8 is a diagram of an example of error encoding and slicingprocessing of the dispersed error encoding in accordance with thepresent invention;

FIG. 9 is a diagram of an example of grouping selection processing ofthe outbound DST processing in accordance with the present invention;

FIG. 10 is a diagram of an example of converting data into slice groupsin accordance with the present invention;

FIG. 11 is a schematic block diagram of an embodiment of a DST executionunit in accordance with the present invention;

FIG. 12 is a schematic block diagram of an example of operation of a DSTexecution unit in accordance with the present invention;

FIG. 13 is a schematic block diagram of an embodiment of an inbounddistributed storage and/or task (DST) processing in accordance with thepresent invention;

FIG. 14 is a logic diagram of an example of a method for inbound DSTprocessing in accordance with the present invention;

FIG. 15 is a diagram of an example of de-grouping selection processingof the inbound DST processing in accordance with the present invention;

FIG. 16 is a schematic block diagram of an embodiment of a dispersederror decoding in accordance with the present invention;

FIG. 17 is a diagram of an example of de-slicing and error decodingprocessing of the dispersed error decoding in accordance with thepresent invention;

FIG. 18 is a diagram of an example of a de-segment processing of thedispersed error decoding in accordance with the present invention;

FIG. 19 is a diagram of an example of converting slice groups into datain accordance with the present invention;

FIG. 20 is a diagram of an example of a distributed storage within thedistributed computing system in accordance with the present invention;

FIG. 21 is a schematic block diagram of an example of operation ofoutbound distributed storage and/or task (DST) processing for storingdata in accordance with the present invention;

FIG. 22 is a schematic block diagram of an example of a dispersed errorencoding for the example of FIG. 21 in accordance with the presentinvention;

FIG. 23 is a diagram of an example of converting data into pillar slicegroups for storage in accordance with the present invention;

FIG. 24 is a schematic block diagram of an example of a storageoperation of a DST execution unit in accordance with the presentinvention;

FIG. 25 is a schematic block diagram of an example of operation ofinbound distributed storage and/or task (DST) processing for retrievingdispersed error encoded data in accordance with the present invention;

FIG. 26 is a schematic block diagram of an example of a dispersed errordecoding for the example of FIG. 25 in accordance with the presentinvention;

FIG. 27 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing a plurality ofdata and a plurality of task codes in accordance with the presentinvention;

FIG. 28 is a schematic block diagram of an example of the distributedcomputing system performing tasks on stored data in accordance with thepresent invention;

FIG. 29 is a schematic block diagram of an embodiment of a taskdistribution module facilitating the example of FIG. 28 in accordancewith the present invention;

FIG. 30 is a diagram of a specific example of the distributed computingsystem performing tasks on stored data in accordance with the presentinvention;

FIG. 31 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing data and taskcodes for the example of FIG. 30 in accordance with the presentinvention;

FIG. 32 is a diagram of an example of DST allocation information for theexample of FIG. 30 in accordance with the present invention;

FIGS. 33-38 are schematic block diagrams of the DSTN module performingthe example of FIG. 30 in accordance with the present invention;

FIG. 39 is a diagram of an example of combining result information intofinal results for the example of FIG. 30 in accordance with the presentinvention;

FIGS. 40A-B are schematic block diagrams of an embodiment of a dispersedstorage network (DSN) illustrating an example of executing tasks inaccordance with the present invention;

FIG. 40C is a flowchart illustrating an example of executing tasks inaccordance with the present invention;

FIGS. 41A, G, and H are schematic block diagrams of another embodimentof a dispersed storage network (DSN) in accordance with the presentinvention;

FIG. 41B is a diagram illustrating an example of encoding a concatenatedobject into a plurality of data blocks in accordance with the presentinvention;

FIG. 41C is a diagram illustrating an example of matrix multiplicationof an encoding matrix and a data matrix using a dispersed storage errorcoding function to produce a coded matrix in accordance with the presentinvention;

FIG. 41D is a diagram illustrating another example of matrixmultiplication of an encoding matrix and a data matrix using a dispersedstorage error coding function to produce a coded matrix in accordancewith the present invention;

FIG. 41E is a diagram illustrating another example of matrixmultiplication of an encoding matrix and a data matrix using a dispersedstorage error coding function to produce a coded matrix in accordancewith the present invention;

FIG. 41F is a diagram illustrating an example of mapping data objects toa concatenated object in accordance with the present invention;

FIG. 41I is a flowchart illustrating an example of concatenating dataobjects for storage in accordance with the present invention;

FIGS. 42A-B are schematic block diagrams of another embodiment of adispersed storage network (DSN) illustrating an example of storing datain accordance with the present invention;

FIG. 42C is a schematic block diagram of another embodiment of adispersed storage network (DSN) illustrating an example of retrievingdata in accordance with the present invention;

FIG. 42D is a flowchart illustrating another example of accessing datain accordance with the present invention;

FIG. 43A is a schematic block diagram of an embodiment of a storageservice access system in accordance with the present invention;

FIG. 43B is a flowchart illustrating an example of authentication accessto a storage service in accordance with the present invention;

FIGS. 44A-B are schematic block diagrams of another embodiment of adispersed storage network (DSN) illustrating another example of storingdata in accordance with the present invention;

FIG. 44C is a flowchart illustrating another example of storing data inaccordance with the present invention;

FIGS. 45A-B are schematic block diagrams of another embodiment of adispersed storage network (DSN) illustrating an example of rebuildingstored data in accordance with the present invention;

FIG. 45C is a flowchart illustrating an example of rebuilding storeddata in accordance with the present invention;

FIGS. 46A-B are schematic block diagrams of another embodiment of adispersed storage network (DSN) illustrating another example of storingdata in accordance with the present invention;

FIG. 46C is a flowchart illustrating another example of storing data inaccordance with the present invention;

FIG. 47A is a schematic block diagram of another embodiment of adispersed storage network (DSN) in accordance with the presentinvention;

FIG. 47B is a flowchart illustrating an example of resolving writeconflicts in accordance with the present invention;

FIG. 48A is a schematic block diagram of another embodiment of adispersed storage network (DSN) in accordance with the presentinvention; and

FIG. 48B is a flowchart illustrating an example of storing a pluralityof correlated data in accordance with the present invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system 10 that includes a user device 12 and/or a user device14, a distributed storage and/or task (DST) processing unit 16, adistributed storage and/or task network (DSTN) managing unit 18, a DSTintegrity processing unit 20, and a distributed storage and/or tasknetwork (DSTN) module 22. The components of the distributed computingsystem 10 are coupled via a network 24, which may include one or morewireless and/or wire lined communication systems; one or more privateintranet systems and/or public internet systems; and/or one or morelocal area networks (LAN) and/or wide area networks (WAN).

The DSTN module 22 includes a plurality of distributed storage and/ortask (DST) execution units 36 that may be located at geographicallydifferent sites (e.g., one in Chicago, one in Milwaukee, etc.). Each ofthe DST execution units is operable to store dispersed error encodeddata and/or to execute, in a distributed manner, one or more tasks ondata. The tasks may be a simple function (e.g., a mathematical function,a logic function, an identify function, a find function, a search enginefunction, a replace function, etc.), a complex function (e.g.,compression, human and/or computer language translation, text-to-voiceconversion, voice-to-text conversion, etc.), multiple simple and/orcomplex functions, one or more algorithms, one or more applications,etc.

Each of the user devices 12-14, the DST processing unit 16, the DSTNmanaging unit 18, and the DST integrity processing unit 20 include acomputing core 26 and may be a portable computing device and/or a fixedcomputing device. A portable computing device may be a social networkingdevice, a gaming device, a cell phone, a smart phone, a personal digitalassistant, a digital music player, a digital video player, a laptopcomputer, a handheld computer, a tablet, a video game controller, and/orany other portable device that includes a computing core. A fixedcomputing device may be a personal computer (PC), a computer server, acable set-top box, a satellite receiver, a television set, a printer, afax machine, home entertainment equipment, a video game console, and/orany type of home or office computing equipment. User device 12 and DSTprocessing unit 16 are configured to include a DST client module 34.

With respect to interfaces, each interface 30, 32, and 33 includessoftware and/or hardware to support one or more communication links viathe network 24 indirectly and/or directly. For example, interface 30supports a communication link (e.g., wired, w0ireless, direct, via aLAN, via the network 24, etc.) between user device 14 and the DSTprocessing unit 16. As another example, interface 32 supportscommunication links (e.g., a wired connection, a wireless connection, aLAN connection, and/or any other type of connection to/from the network24) between user device 12 and the DSTN module 22 and between the DSTprocessing unit 16 and the DSTN module 22. As yet another example,interface 33 supports a communication link for each of the DSTN managingunit 18 and DST integrity processing unit 20 to the network 24.

The distributed computing system 10 is operable to support dispersedstorage (DS) error encoded data storage and retrieval, to supportdistributed task processing on received data, and/or to supportdistributed task processing on stored data. In general and with respectto DS error encoded data storage and retrieval, the distributedcomputing system 10 supports three primary operations: storagemanagement, data storage and retrieval (an example of which will bediscussed with reference to FIGS. 20-26), and data storage integrityverification. In accordance with these three primary functions, data canbe encoded, distributedly stored in physically different locations, andsubsequently retrieved in a reliable and secure manner. Such a system istolerant of a significant number of failures (e.g., up to a failurelevel, which may be greater than or equal to a pillar width minus adecode threshold minus one) that may result from individual storagedevice failures and/or network equipment failures without loss of dataand without the need for a redundant or backup copy. Further, the systemallows the data to be stored for an indefinite period of time withoutdata loss and does so in a secure manner (e.g., the system is veryresistant to attempts at hacking the data).

The second primary function (i.e., distributed data storage andretrieval) begins and ends with a user device 12-14. For instance, if asecond type of user device 14 has data 40 to store in the DSTN module22, it sends the data 40 to the DST processing unit 16 via its interface30. The interface 30 functions to mimic a conventional operating system(OS) file system interface (e.g., network file system (NFS), flash filesystem (FFS), disk file system (DFS), file transfer protocol (FTP),web-based distributed authoring and versioning (WebDAV), etc.) and/or ablock memory interface (e.g., small computer system interface (SCSI),internet small computer system interface (iSCSI), etc.). In addition,the interface 30 may attach a user identification code (ID) to the data40.

To support storage management, the DSTN managing unit 18 performs DSmanagement services. One such DS management service includes the DSTNmanaging unit 18 establishing distributed data storage parameters (e.g.,vault creation, distributed storage parameters, security parameters,billing information, user profile information, etc.) for a user device12-14 individually or as part of a group of user devices. For example,the DSTN managing unit 18 coordinates creation of a vault (e.g., avirtual memory block) within memory of the DSTN module 22 for a userdevice, a group of devices, or for public access and establishes pervault dispersed storage (DS) error encoding parameters for a vault. TheDSTN managing unit 18 may facilitate storage of DS error encodingparameters for each vault of a plurality of vaults by updating registryinformation for the distributed computing system 10. The facilitatingincludes storing updated registry information in one or more of the DSTNmodule 22, the user device 12, the DST processing unit 16, and the DSTintegrity processing unit 20.

The DS error encoding parameters (e.g., or dispersed storage errorcoding parameters) include data segmenting information (e.g., how manysegments data (e.g., a file, a group of files, a data block, etc.) isdivided into), segment security information (e.g., per segmentencryption, compression, integrity checksum, etc.), error codinginformation (e.g., pillar width, decode threshold, read threshold, writethreshold, etc.), slicing information (e.g., the number of encoded dataslices that will be created for each data segment); and slice securityinformation (e.g., per encoded data slice encryption, compression,integrity checksum, etc.).

The DSTN managing unit 18 creates and stores user profile information(e.g., an access control list (ACL)) in local memory and/or withinmemory of the DSTN module 22. The user profile information includesauthentication information, permissions, and/or the security parameters.The security parameters may include encryption/decryption scheme, one ormore encryption keys, key generation scheme, and/or dataencoding/decoding scheme.

The DSTN managing unit 18 creates billing information for a particularuser, a user group, a vault access, public vault access, etc. Forinstance, the DSTN managing unit 18 tracks the number of times a useraccesses a private vault and/or public vaults, which can be used togenerate a per-access billing information. In another instance, the DSTNmanaging unit 18 tracks the amount of data stored and/or retrieved by auser device and/or a user group, which can be used to generate aper-data-amount billing information.

Another DS management service includes the DSTN managing unit 18performing network operations, network administration, and/or networkmaintenance. Network operations includes authenticating user dataallocation requests (e.g., read and/or write requests), managingcreation of vaults, establishing authentication credentials for userdevices, adding/deleting components (e.g., user devices, DST executionunits, and/or DST processing units) from the distributed computingsystem 10, and/or establishing authentication credentials for DSTexecution units 36. Network administration includes monitoring devicesand/or units for failures, maintaining vault information, determiningdevice and/or unit activation status, determining device and/or unitloading, and/or determining any other system level operation thataffects the performance level of the system 10. Network maintenanceincludes facilitating replacing, upgrading, repairing, and/or expandinga device and/or unit of the system 10.

To support data storage integrity verification within the distributedcomputing system 10, the DST integrity processing unit 20 performsrebuilding of ‘bad’ or missing encoded data slices. At a high level, theDST integrity processing unit 20 performs rebuilding by periodicallyattempting to retrieve/list encoded data slices, and/or slice names ofthe encoded data slices, from the DSTN module 22. For retrieved encodedslices, they are checked for errors due to data corruption, outdatedversion, etc. If a slice includes an error, it is flagged as a ‘bad’slice. For encoded data slices that were not received and/or not listed,they are flagged as missing slices. Bad and/or missing slices aresubsequently rebuilt using other retrieved encoded data slices that aredeemed to be good slices to produce rebuilt slices. The rebuilt slicesare stored in memory of the DSTN module 22. Note that the DST integrityprocessing unit 20 may be a separate unit as shown, it may be includedin the DSTN module 22, it may be included in the DST processing unit 16,and/or distributed among the DST execution units 36.

To support distributed task processing on received data, the distributedcomputing system 10 has two primary operations: DST (distributed storageand/or task processing) management and DST execution on received data(an example of which will be discussed with reference to FIGS. 3-19).With respect to the storage portion of the DST management, the DSTNmanaging unit 18 functions as previously described. With respect to thetasking processing of the DST management, the DSTN managing unit 18performs distributed task processing (DTP) management services. One suchDTP management service includes the DSTN managing unit 18 establishingDTP parameters (e.g., user-vault affiliation information, billinginformation, user-task information, etc.) for a user device 12-14individually or as part of a group of user devices.

Another DTP management service includes the DSTN managing unit 18performing DTP network operations, network administration (which isessentially the same as described above), and/or network maintenance(which is essentially the same as described above). Network operationsinclude, but are not limited to, authenticating user task processingrequests (e.g., valid request, valid user, etc.), authenticating resultsand/or partial results, establishing DTP authentication credentials foruser devices, adding/deleting components (e.g., user devices, DSTexecution units, and/or DST processing units) from the distributedcomputing system, and/or establishing DTP authentication credentials forDST execution units.

To support distributed task processing on stored data, the distributedcomputing system 10 has two primary operations: DST (distributed storageand/or task) management and DST execution on stored data. With respectto the DST execution on stored data, if the second type of user device14 has a task request 38 for execution by the DSTN module 22, it sendsthe task request 38 to the DST processing unit 16 via its interface 30.An example of DST execution on stored data will be discussed in greaterdetail with reference to FIGS. 27-39. With respect to the DSTmanagement, it is substantially similar to the DST management to supportdistributed task processing on received data.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (TO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one IO device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSTN interface module 76.

The DSTN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). TheDSTN interface module 76 and/or the network interface module 70 mayfunction as the interface 30 of the user device 14 of FIG. 1. Furthernote that the IO device interface module 62 and/or the memory interfacemodules may be collectively or individually referred to as IO ports.

FIG. 3 is a diagram of an example of the distributed computing systemperforming a distributed storage and task processing operation. Thedistributed computing system includes a DST (distributed storage and/ortask) client module 34 (which may be in user device 14 and/or in DSTprocessing unit 16 of FIG. 1), a network 24, a plurality of DSTexecution units 1-n that includes two or more DST execution units 36 ofFIG. 1 (which form at least a portion of DSTN module 22 of FIG. 1), aDST managing module (not shown), and a DST integrity verification module(not shown). The DST client module 34 includes an outbound DSTprocessing section 80 and an inbound DST processing section 82. Each ofthe DST execution units 1-n includes a controller 86, a processingmodule 84, memory 88, a DT (distributed task) execution module 90, and aDST client module 34.

In an example of operation, the DST client module 34 receives data 92and one or more tasks 94 to be performed upon the data 92. The data 92may be of any size and of any content, where, due to the size (e.g.,greater than a few Terabytes), the content (e.g., secure data, etc.),and/or task(s) (e.g., MIPS intensive), distributed processing of thetask(s) on the data is desired. For example, the data 92 may be one ormore digital books, a copy of a company's emails, a large-scale Internetsearch, a video security file, one or more entertainment video files(e.g., television programs, movies, etc.), data files, and/or any otherlarge amount of data (e.g., greater than a few Terabytes).

Within the DST client module 34, the outbound DST processing section 80receives the data 92 and the task(s) 94. The outbound DST processingsection 80 processes the data 92 to produce slice groupings 96. As anexample of such processing, the outbound DST processing section 80partitions the data 92 into a plurality of data partitions. For eachdata partition, the outbound DST processing section 80 dispersed storage(DS) error encodes the data partition to produce encoded data slices andgroups the encoded data slices into a slice grouping 96. In addition,the outbound DST processing section 80 partitions the task 94 intopartial tasks 98, where the number of partial tasks 98 may correspond tothe number of slice groupings 96.

The outbound DST processing section 80 then sends, via the network 24,the slice groupings 96 and the partial tasks 98 to the DST executionunits 1-n of the DSTN module 22 of FIG. 1. For example, the outbound DSTprocessing section 80 sends slice group 1 and partial task 1 to DSTexecution unit 1. As another example, the outbound DST processingsection 80 sends slice group #n and partial task #n to DST executionunit #n.

Each DST execution unit performs its partial task 98 upon its slicegroup 96 to produce partial results 102. For example, DST execution unit#1 performs partial task #1 on slice group #1 to produce a partialresult #1, for results. As a more specific example, slice group #1corresponds to a data partition of a series of digital books and thepartial task #1 corresponds to searching for specific phrases, recordingwhere the phrase is found, and establishing a phrase count. In this morespecific example, the partial result #1 includes information as to wherethe phrase was found and includes the phrase count.

Upon completion of generating their respective partial results 102, theDST execution units send, via the network 24, their partial results 102to the inbound DST processing section 82 of the DST client module 34.The inbound DST processing section 82 processes the received partialresults 102 to produce a result 104. Continuing with the specificexample of the preceding paragraph, the inbound DST processing section82 combines the phrase count from each of the DST execution units 36 toproduce a total phrase count. In addition, the inbound DST processingsection 82 combines the ‘where the phrase was found’ information fromeach of the DST execution units 36 within their respective datapartitions to produce ‘where the phrase was found’ information for theseries of digital books.

In another example of operation, the DST client module 34 requestsretrieval of stored data within the memory of the DST execution units 36(e.g., memory of the DSTN module). In this example, the task 94 isretrieve data stored in the memory of the DSTN module. Accordingly, theoutbound DST processing section 80 converts the task 94 into a pluralityof partial tasks 98 and sends the partial tasks 98 to the respective DSTexecution units 1-n.

In response to the partial task 98 of retrieving stored data, a DSTexecution unit 36 identifies the corresponding encoded data slices 100and retrieves them. For example, DST execution unit #1 receives partialtask #1 and retrieves, in response thereto, retrieved slices #1. The DSTexecution units 36 send their respective retrieved slices 100 to theinbound DST processing section 82 via the network 24.

The inbound DST processing section 82 converts the retrieved slices 100into data 92. For example, the inbound DST processing section 82de-groups the retrieved slices 100 to produce encoded slices per datapartition. The inbound DST processing section 82 then DS error decodesthe encoded slices per data partition to produce data partitions. Theinbound DST processing section 82 de-partitions the data partitions torecapture the data 92.

FIG. 4 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing section 80 of a DSTclient module 34 FIG. 1 coupled to a DSTN module 22 of a FIG. 1 (e.g., aplurality of n DST execution units 36) via a network 24. The outboundDST processing section 80 includes a data partitioning module 110, adispersed storage (DS) error encoding module 112, a grouping selectormodule 114, a control module 116, and a distributed task control module118.

In an example of operation, the data partitioning module 110 partitionsdata 92 into a plurality of data partitions 120. The number ofpartitions and the size of the partitions may be selected by the controlmodule 116 via control 160 based on the data 92 (e.g., its size, itscontent, etc.), a corresponding task 94 to be performed (e.g., simple,complex, single step, multiple steps, etc.), DS encoding parameters(e.g., pillar width, decode threshold, write threshold, segment securityparameters, slice security parameters, etc.), capabilities of the DSTexecution units 36 (e.g., processing resources, availability ofprocessing recourses, etc.), and/or as may be inputted by a user, systemadministrator, or other operator (human or automated). For example, thedata partitioning module 110 partitions the data 92 (e.g., 100Terabytes) into 100,000 data segments, each being 1 Gigabyte in size.Alternatively, the data partitioning module 110 partitions the data 92into a plurality of data segments, where some of data segments are of adifferent size, are of the same size, or a combination thereof.

The DS error encoding module 112 receives the data partitions 120 in aserial manner, a parallel manner, and/or a combination thereof. For eachdata partition 120, the DS error encoding module 112 DS error encodesthe data partition 120 in accordance with control information 160 fromthe control module 116 to produce encoded data slices 122. The DS errorencoding includes segmenting the data partition into data segments,segment security processing (e.g., encryption, compression,watermarking, integrity check (e.g., CRC), etc.), error encoding,slicing, and/or per slice security processing (e.g., encryption,compression, watermarking, integrity check (e.g., CRC), etc.). Thecontrol information 160 indicates which steps of the DS error encodingare active for a given data partition and, for active steps, indicatesthe parameters for the step. For example, the control information 160indicates that the error encoding is active and includes error encodingparameters (e.g., pillar width, decode threshold, write threshold, readthreshold, type of error encoding, etc.).

The grouping selector module 114 groups the encoded slices 122 of a datapartition into a set of slice groupings 96. The number of slicegroupings corresponds to the number of DST execution units 36 identifiedfor a particular task 94. For example, if five DST execution units 36are identified for the particular task 94, the grouping selector modulegroups the encoded slices 122 of a data partition into five slicegroupings 96. The grouping selector module 114 outputs the slicegroupings 96 to the corresponding DST execution units 36 via the network24.

The distributed task control module 118 receives the task 94 andconverts the task 94 into a set of partial tasks 98. For example, thedistributed task control module 118 receives a task to find where in thedata (e.g., a series of books) a phrase occurs and a total count of thephrase usage in the data. In this example, the distributed task controlmodule 118 replicates the task 94 for each DST execution unit 36 toproduce the partial tasks 98. In another example, the distributed taskcontrol module 118 receives a task to find where in the data a firstphrase occurs, where in the data a second phrase occurs, and a totalcount for each phrase usage in the data. In this example, thedistributed task control module 118 generates a first set of partialtasks 98 for finding and counting the first phrase and a second set ofpartial tasks for finding and counting the second phrase. Thedistributed task control module 118 sends respective first and/or secondpartial tasks 98 to each DST execution unit 36.

FIG. 5 is a logic diagram of an example of a method for outbounddistributed storage and task (DST) processing that begins at step 126where a DST client module receives data and one or more correspondingtasks. The method continues at step 128 where the DST client moduledetermines a number of DST units to support the task for one or moredata partitions. For example, the DST client module may determine thenumber of DST units to support the task based on the size of the data,the requested task, the content of the data, a predetermined number(e.g., user indicated, system administrator determined, etc.), availableDST units, capability of the DST units, and/or any other factorregarding distributed task processing of the data. The DST client modulemay select the same DST units for each data partition, may selectdifferent DST units for the data partitions, or a combination thereof.

The method continues at step 130 where the DST client module determinesprocessing parameters of the data based on the number of DST unitsselected for distributed task processing. The processing parametersinclude data partitioning information, DS encoding parameters, and/orslice grouping information. The data partitioning information includes anumber of data partitions, size of each data partition, and/ororganization of the data partitions (e.g., number of data blocks in apartition, the size of the data blocks, and arrangement of the datablocks). The DS encoding parameters include segmenting information,segment security information, error encoding information (e.g.,dispersed storage error encoding function parameters including one ormore of pillar width, decode threshold, write threshold, read threshold,generator matrix), slicing information, and/or per slice securityinformation. The slice grouping information includes informationregarding how to arrange the encoded data slices into groups for theselected DST units. As a specific example, if the DST client moduledetermines that five DST units are needed to support the task, then itdetermines that the error encoding parameters include a pillar width offive and a decode threshold of three.

The method continues at step 132 where the DST client module determinestask partitioning information (e.g., how to partition the tasks) basedon the selected DST units and data processing parameters. The dataprocessing parameters include the processing parameters and DST unitcapability information. The DST unit capability information includes thenumber of DT (distributed task) execution units, execution capabilitiesof each DT execution unit (e.g., MIPS capabilities, processing resources(e.g., quantity and capability of microprocessors, CPUs, digital signalprocessors, co-processor, microcontrollers, arithmetic logic circuitry,and/or any other analog and/or digital processing circuitry),availability of the processing resources, memory information (e.g.,type, size, availability, etc.)), and/or any information germane toexecuting one or more tasks.

The method continues at step 134 where the DST client module processesthe data in accordance with the processing parameters to produce slicegroupings. The method continues at step 136 where the DST client modulepartitions the task based on the task partitioning information toproduce a set of partial tasks. The method continues at step 138 wherethe DST client module sends the slice groupings and the correspondingpartial tasks to respective DST units.

FIG. 6 is a schematic block diagram of an embodiment of the dispersedstorage (DS) error encoding module 112 of an outbound distributedstorage and task (DST) processing section. The DS error encoding module112 includes a segment processing module 142, a segment securityprocessing module 144, an error encoding module 146, a slicing module148, and a per slice security processing module 150. Each of thesemodules is coupled to a control module 116 to receive controlinformation 160 therefrom.

In an example of operation, the segment processing module 142 receives adata partition 120 from a data partitioning module and receivessegmenting information as the control information 160 from the controlmodule 116. The segmenting information indicates how the segmentprocessing module 142 is to segment the data partition 120. For example,the segmenting information indicates how many rows to segment the databased on a decode threshold of an error encoding scheme, indicates howmany columns to segment the data into based on a number and size of datablocks within the data partition 120, and indicates how many columns toinclude in a data segment 152. The segment processing module 142segments the data 120 into data segments 152 in accordance with thesegmenting information.

The segment security processing module 144, when enabled by the controlmodule 116, secures the data segments 152 based on segment securityinformation received as control information 160 from the control module116. The segment security information includes data compression,encryption, watermarking, integrity check (e.g., cyclic redundancy check(CRC), etc.), and/or any other type of digital security. For example,when the segment security processing module 144 is enabled, it maycompress a data segment 152, encrypt the compressed data segment, andgenerate a CRC value for the encrypted data segment to produce a securedata segment 154. When the segment security processing module 144 is notenabled, it passes the data segments 152 to the error encoding module146 or is bypassed such that the data segments 152 are provided to theerror encoding module 146.

The error encoding module 146 encodes the secure data segments 154 inaccordance with error correction encoding parameters received as controlinformation 160 from the control module 116. The error correctionencoding parameters (e.g., also referred to as dispersed storage errorcoding parameters) include identifying an error correction encodingscheme (e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an online coding algorithm, an information dispersalalgorithm, etc.), a pillar width, a decode threshold, a read threshold,a write threshold, etc. For example, the error correction encodingparameters identify a specific error correction encoding scheme,specifies a pillar width of five, and specifies a decode threshold ofthree. From these parameters, the error encoding module 146 encodes adata segment 154 to produce an encoded data segment 156.

The slicing module 148 slices the encoded data segment 156 in accordancewith the pillar width of the error correction encoding parametersreceived as control information 160. For example, if the pillar width isfive, the slicing module 148 slices an encoded data segment 156 into aset of five encoded data slices. As such, for a plurality of encodeddata segments 156 for a given data partition, the slicing module outputsa plurality of sets of encoded data slices 158. The per slice securityprocessing module 150, when enabled by the control module 116, secureseach encoded data slice 158 based on slice security information receivedas control information 160 from the control module 116. The slicesecurity information includes data compression, encryption,watermarking, integrity check (e.g., CRC, etc.), and/or any other typeof digital security. For example, when the per slice security processingmodule 150 is enabled, it compresses an encoded data slice 158, encryptsthe compressed encoded data slice, and generates a CRC value for theencrypted encoded data slice to produce a secure encoded data slice 122.When the per slice security processing module 150 is not enabled, itpasses the encoded data slices 158 or is bypassed such that the encodeddata slices 158 are the output of the DS error encoding module 112. Notethat the control module 116 may be omitted and each module stores itsown parameters.

FIG. 7 is a diagram of an example of a segment processing of a dispersedstorage (DS) error encoding module. In this example, a segmentprocessing module 142 receives a data partition 120 that includes 45data blocks (e.g., d1-d45), receives segmenting information (i.e.,control information 160) from a control module, and segments the datapartition 120 in accordance with the control information 160 to producedata segments 152. Each data block may be of the same size as other datablocks or of a different size. In addition, the size of each data blockmay be a few bytes to megabytes of data. As previously mentioned, thesegmenting information indicates how many rows to segment the datapartition into, indicates how many columns to segment the data partitioninto, and indicates how many columns to include in a data segment.

In this example, the decode threshold of the error encoding scheme isthree; as such the number of rows to divide the data partition into isthree. The number of columns for each row is set to 15, which is basedon the number and size of data blocks. The data blocks of the datapartition are arranged in rows and columns in a sequential order (i.e.,the first row includes the first 15 data blocks; the second row includesthe second 15 data blocks; and the third row includes the last 15 datablocks).

With the data blocks arranged into the desired sequential order, theyare divided into data segments based on the segmenting information. Inthis example, the data partition is divided into 8 data segments; thefirst 7 include 2 columns of three rows and the last includes 1 columnof three rows. Note that the first row of the 8 data segments is insequential order of the first 15 data blocks; the second row of the 8data segments in sequential order of the second 15 data blocks; and thethird row of the 8 data segments in sequential order of the last 15 datablocks. Note that the number of data blocks, the grouping of the datablocks into segments, and size of the data blocks may vary toaccommodate the desired distributed task processing function.

FIG. 8 is a diagram of an example of error encoding and slicingprocessing of the dispersed error encoding processing the data segmentsof FIG. 7. In this example, data segment 1 includes 3 rows with each rowbeing treated as one word for encoding. As such, data segment 1 includesthree words for encoding: word 1 including data blocks d1 and d2, word 2including data blocks d16 and d17, and word 3 including data blocks d31and d32. Each of data segments 2-7 includes three words where each wordincludes two data blocks. Data segment 8 includes three words where eachword includes a single data block (e.g., d15, d30, and d45).

In operation, an error encoding module 146 and a slicing module 148convert each data segment into a set of encoded data slices inaccordance with error correction encoding parameters as controlinformation 160. More specifically, when the error correction encodingparameters indicate a unity matrix Reed-Solomon based encodingalgorithm, 5 pillars, and decode threshold of 3, the first three encodeddata slices of the set of encoded data slices for a data segment aresubstantially similar to the corresponding word of the data segment. Forinstance, when the unity matrix Reed-Solomon based encoding algorithm isapplied to data segment 1, the content of the first encoded data slice(DS1_d1&2) of the first set of encoded data slices (e.g., correspondingto data segment 1) is substantially similar to content of the first word(e.g., d1 & d2); the content of the second encoded data slice(DS1_d16&17) of the first set of encoded data slices is substantiallysimilar to content of the second word (e.g., d16 & d17); and the contentof the third encoded data slice (DS1_d31&32) of the first set of encodeddata slices is substantially similar to content of the third word (e.g.,d31 & d32).

The content of the fourth and fifth encoded data slices (e.g., ES1_1 andES1_2) of the first set of encoded data slices include error correctiondata based on the first-third words of the first data segment. With suchan encoding and slicing scheme, retrieving any three of the five encodeddata slices allows the data segment to be accurately reconstructed.

The encoding and slicing of data segments 2-7 yield sets of encoded dataslices similar to the set of encoded data slices of data segment 1. Forinstance, the content of the first encoded data slice (DS2_d3&4) of thesecond set of encoded data slices (e.g., corresponding to data segment2) is substantially similar to content of the first word (e.g., d3 &d4); the content of the second encoded data slice (DS2_d18&19) of thesecond set of encoded data slices is substantially similar to content ofthe second word (e.g., d18 & d19); and the content of the third encodeddata slice (DS2_d33&34) of the second set of encoded data slices issubstantially similar to content of the third word (e.g., d33 & d34).The content of the fourth and fifth encoded data slices (e.g., ES1_1 andES1_2) of the second set of encoded data slices includes errorcorrection data based on the first-third words of the second datasegment.

FIG. 9 is a diagram of an example of grouping selection processing of anoutbound distributed storage and task (DST) processing in accordancewith grouping selector information as control information 160 from acontrol module. Encoded slices for data partition 122 are grouped inaccordance with the control information 160 to produce slice groupings96. In this example, a grouping selector module 114 organizes theencoded data slices into five slice groupings (e.g., one for each DSTexecution unit of a distributed storage and task network (DSTN) module).As a specific example, the grouping selector module 114 creates a firstslice grouping for a DST execution unit #1, which includes first encodedslices of each of the sets of encoded slices. As such, the first DSTexecution unit receives encoded data slices corresponding to data blocks1-15 (e.g., encoded data slices of contiguous data).

The grouping selector module 114 also creates a second slice groupingfor a DST execution unit #2, which includes second encoded slices ofeach of the sets of encoded slices. As such, the second DST executionunit receives encoded data slices corresponding to data blocks 16-30.The grouping selector module 114 further creates a third slice groupingfor DST execution unit #3, which includes third encoded slices of eachof the sets of encoded slices. As such, the third DST execution unitreceives encoded data slices corresponding to data blocks 31-45.

The grouping selector module 114 creates a fourth slice grouping for DSTexecution unit #4, which includes fourth encoded slices of each of thesets of encoded slices. As such, the fourth DST execution unit receivesencoded data slices corresponding to first error encoding information(e.g., encoded data slices of error coding (EC) data). The groupingselector module 114 further creates a fifth slice grouping for DSTexecution unit #5, which includes fifth encoded slices of each of thesets of encoded slices. As such, the fifth DST execution unit receivesencoded data slices corresponding to second error encoding information.

FIG. 10 is a diagram of an example of converting data 92 into slicegroups that expands on the preceding figures. As shown, the data 92 ispartitioned in accordance with a partitioning function 164 into aplurality of data partitions (1-x, where x is an integer greater than4). Each data partition (or chunkset of data) is encoded and groupedinto slice groupings as previously discussed by an encoding and groupingfunction 166. For a given data partition, the slice groupings are sentto distributed storage and task (DST) execution units. From datapartition to data partition, the ordering of the slice groupings to theDST execution units may vary.

For example, the slice groupings of data partition #1 is sent to the DSTexecution units such that the first DST execution receives first encodeddata slices of each of the sets of encoded data slices, whichcorresponds to a first continuous data chunk of the first data partition(e.g., refer to FIG. 9), a second DST execution receives second encodeddata slices of each of the sets of encoded data slices, whichcorresponds to a second continuous data chunk of the first datapartition, etc.

For the second data partition, the slice groupings may be sent to theDST execution units in a different order than it was done for the firstdata partition. For instance, the first slice grouping of the seconddata partition (e.g., slice group 2_1) is sent to the second DSTexecution unit; the second slice grouping of the second data partition(e.g., slice group 2_2) is sent to the third DST execution unit; thethird slice grouping of the second data partition (e.g., slice group2_3) is sent to the fourth DST execution unit; the fourth slice groupingof the second data partition (e.g., slice group 2_4, which includesfirst error coding information) is sent to the fifth DST execution unit;and the fifth slice grouping of the second data partition (e.g., slicegroup 2_5, which includes second error coding information) is sent tothe first DST execution unit.

The pattern of sending the slice groupings to the set of DST executionunits may vary in a predicted pattern, a random pattern, and/or acombination thereof from data partition to data partition. In addition,from data partition to data partition, the set of DST execution unitsmay change. For example, for the first data partition, DST executionunits 1-5 may be used; for the second data partition, DST executionunits 6-10 may be used; for the third data partition, DST executionunits 3-7 may be used; etc. As is also shown, the task is divided intopartial tasks that are sent to the DST execution units in conjunctionwith the slice groupings of the data partitions.

FIG. 11 is a schematic block diagram of an embodiment of a DST(distributed storage and/or task) execution unit that includes aninterface 169, a controller 86, memory 88, one or more DT (distributedtask) execution modules 90, and a DST client module 34. The memory 88 isof sufficient size to store a significant number of encoded data slices(e.g., thousands of slices to hundreds-of-millions of slices) and mayinclude one or more hard drives and/or one or more solid-state memorydevices (e.g., flash memory, DRAM, etc.).

In an example of storing a slice group, the DST execution modulereceives a slice grouping 96 (e.g., slice group #1) via interface 169.The slice grouping 96 includes, per partition, encoded data slices ofcontiguous data or encoded data slices of error coding (EC) data. Forslice group #1, the DST execution module receives encoded data slices ofcontiguous data for partitions #1 and #x (and potentially others between3 and x) and receives encoded data slices of EC data for partitions #2and #3 (and potentially others between 3 and x). Examples of encodeddata slices of contiguous data and encoded data slices of error coding(EC) data are discussed with reference to FIG. 9. The memory 88 storesthe encoded data slices of slice groupings 96 in accordance with memorycontrol information 174 it receives from the controller 86.

The controller 86 (e.g., a processing module, a CPU, etc.) generates thememory control information 174 based on a partial task(s) 98 anddistributed computing information (e.g., user information (e.g., userID, distributed computing permissions, data access permission, etc.),vault information (e.g., virtual memory assigned to user, user group,temporary storage for task processing, etc.), task validationinformation, etc.). For example, the controller 86 interprets thepartial task(s) 98 in light of the distributed computing information todetermine whether a requestor is authorized to perform the task 98, isauthorized to access the data, and/or is authorized to perform the taskon this particular data. When the requestor is authorized, thecontroller 86 determines, based on the task 98 and/or another input,whether the encoded data slices of the slice grouping 96 are to betemporarily stored or permanently stored. Based on the foregoing, thecontroller 86 generates the memory control information 174 to write theencoded data slices of the slice grouping 96 into the memory 88 and toindicate whether the slice grouping 96 is permanently stored ortemporarily stored.

With the slice grouping 96 stored in the memory 88, the controller 86facilitates execution of the partial task(s) 98. In an example, thecontroller 86 interprets the partial task 98 in light of thecapabilities of the DT execution module(s) 90. The capabilities includeone or more of MIPS capabilities, processing resources (e.g., quantityand capability of microprocessors, CPUs, digital signal processors,co-processor, microcontrollers, arithmetic logic circuitry, and/or anyother analog and/or digital processing circuitry), availability of theprocessing resources, etc. If the controller 86 determines that the DTexecution module(s) 90 have sufficient capabilities, it generates taskcontrol information 176.

The task control information 176 may be a generic instruction (e.g.,perform the task on the stored slice grouping) or a series ofoperational codes. In the former instance, the DT execution module 90includes a co-processor function specifically configured (fixed orprogrammed) to perform the desired task 98. In the latter instance, theDT execution module 90 includes a general processor topology where thecontroller stores an algorithm corresponding to the particular task 98.In this instance, the controller 86 provides the operational codes(e.g., assembly language, source code of a programming language, objectcode, etc.) of the algorithm to the DT execution module 90 forexecution.

Depending on the nature of the task 98, the DT execution module 90 maygenerate intermediate partial results 102 that are stored in the memory88 or in a cache memory (not shown) within the DT execution module 90.In either case, when the DT execution module 90 completes execution ofthe partial task 98, it outputs one or more partial results 102. Thepartial results 102 may also be stored in memory 88.

If, when the controller 86 is interpreting whether capabilities of theDT execution module(s) 90 can support the partial task 98, thecontroller 86 determines that the DT execution module(s) 90 cannotadequately support the task 98 (e.g., does not have the right resources,does not have sufficient available resources, available resources wouldbe too slow, etc.), it then determines whether the partial task 98should be fully offloaded or partially offloaded.

If the controller 86 determines that the partial task 98 should be fullyoffloaded, it generates DST control information 178 and provides it tothe DST client module 34. The DST control information 178 includes thepartial task 98, memory storage information regarding the slice grouping96, and distribution instructions. The distribution instructionsinstruct the DST client module 34 to divide the partial task 98 intosub-partial tasks 172, to divide the slice grouping 96 into sub-slicegroupings 170, and identify other DST execution units. The DST clientmodule 34 functions in a similar manner as the DST client module 34 ofFIGS. 3-10 to produce the sub-partial tasks 172 and the sub-slicegroupings 170 in accordance with the distribution instructions.

The DST client module 34 receives DST feedback 168 (e.g., sub-partialresults), via the interface 169, from the DST execution units to whichthe task was offloaded. The DST client module 34 provides thesub-partial results to the DST execution unit, which processes thesub-partial results to produce the partial result(s) 102.

If the controller 86 determines that the partial task 98 should bepartially offloaded, it determines what portion of the task 98 and/orslice grouping 96 should be processed locally and what should beoffloaded. For the portion that is being locally processed, thecontroller 86 generates task control information 176 as previouslydiscussed. For the portion that is being offloaded, the controller 86generates DST control information 178 as previously discussed.

When the DST client module 34 receives DST feedback 168 (e.g.,sub-partial results) from the DST executions units to which a portion ofthe task was offloaded, it provides the sub-partial results to the DTexecution module 90. The DT execution module 90 processes thesub-partial results with the sub-partial results it created to producethe partial result(s) 102.

The memory 88 may be further utilized to retrieve one or more of storedslices 100, stored results 104, partial results 102 when the DTexecution module 90 stores partial results 102 and/or results 104 in thememory 88. For example, when the partial task 98 includes a retrievalrequest, the controller 86 outputs the memory control 174 to the memory88 to facilitate retrieval of slices 100 and/or results 104.

FIG. 12 is a schematic block diagram of an example of operation of adistributed storage and task (DST) execution unit storing encoded dataslices and executing a task thereon. To store the encoded data slices ofa partition 1 of slice grouping 1, a controller 86 generates writecommands as memory control information 174 such that the encoded slicesare stored in desired locations (e.g., permanent or temporary) withinmemory 88.

Once the encoded slices are stored, the controller 86 provides taskcontrol information 176 to a distributed task (DT) execution module 90.As a first step of executing the task in accordance with the taskcontrol information 176, the DT execution module 90 retrieves theencoded slices from memory 88. The DT execution module 90 thenreconstructs contiguous data blocks of a data partition. As shown forthis example, reconstructed contiguous data blocks of data partition 1include data blocks 1-15 (e.g., d1-d15).

With the contiguous data blocks reconstructed, the DT execution module90 performs the task on the reconstructed contiguous data blocks. Forexample, the task may be to search the reconstructed contiguous datablocks for a particular word or phrase, identify where in thereconstructed contiguous data blocks the particular word or phraseoccurred, and/or count the occurrences of the particular word or phraseon the reconstructed contiguous data blocks. The DST execution unitcontinues in a similar manner for the encoded data slices of otherpartitions in slice grouping 1. Note that with using the unity matrixerror encoding scheme previously discussed, if the encoded data slicesof contiguous data are uncorrupted, the decoding of them is a relativelystraightforward process of extracting the data.

If, however, an encoded data slice of contiguous data is corrupted (ormissing), it can be rebuilt by accessing other DST execution units thatare storing the other encoded data slices of the set of encoded dataslices of the corrupted encoded data slice. In this instance, the DSTexecution unit having the corrupted encoded data slices retrieves atleast three encoded data slices (of contiguous data and of error codingdata) in the set from the other DST execution units (recall for thisexample, the pillar width is 5 and the decode threshold is 3). The DSTexecution unit decodes the retrieved data slices using the DS errorencoding parameters to recapture the corresponding data segment. The DSTexecution unit then re-encodes the data segment using the DS errorencoding parameters to rebuild the corrupted encoded data slice. Oncethe encoded data slice is rebuilt, the DST execution unit functions aspreviously described.

FIG. 13 is a schematic block diagram of an embodiment of an inbounddistributed storage and/or task (DST) processing section 82 of a DSTclient module coupled to DST execution units of a distributed storageand task network (DSTN) module via a network 24. The inbound DSTprocessing section 82 includes a de-grouping module 180, a DS (dispersedstorage) error decoding module 182, a data de-partitioning module 184, acontrol module 186, and a distributed task control module 188. Note thatthe control module 186 and/or the distributed task control module 188may be separate modules from corresponding ones of outbound DSTprocessing section or may be the same modules.

In an example of operation, the DST execution units have completedexecution of corresponding partial tasks on the corresponding slicegroupings to produce partial results 102. The inbound DST processingsection 82 receives the partial results 102 via the distributed taskcontrol module 188. The inbound DST processing section 82 then processesthe partial results 102 to produce a final result, or results 104. Forexample, if the task was to find a specific word or phrase within data,the partial results 102 indicate where in each of the prescribedportions of the data the corresponding DST execution units found thespecific word or phrase. The distributed task control module 188combines the individual partial results 102 for the correspondingportions of the data into a final result 104 for the data as a whole.

In another example of operation, the inbound DST processing section 82is retrieving stored data from the DST execution units (i.e., the DSTNmodule). In this example, the DST execution units output encoded dataslices 100 corresponding to the data retrieval requests. The de-groupingmodule 180 receives retrieved slices 100 and de-groups them to produceencoded data slices per data partition 122. The DS error decoding module182 decodes, in accordance with DS error encoding parameters, theencoded data slices per data partition 122 to produce data partitions120.

The data de-partitioning module 184 combines the data partitions 120into the data 92. The control module 186 controls the conversion ofretrieved slices 100 into the data 92 using control signals 190 to eachof the modules. For instance, the control module 186 providesde-grouping information to the de-grouping module 180, provides the DSerror encoding parameters to the DS error decoding module 182, andprovides de-partitioning information to the data de-partitioning module184.

FIG. 14 is a logic diagram of an example of a method that is executableby distributed storage and task (DST) client module regarding inboundDST processing. The method begins at step 194 where the DST clientmodule receives partial results. The method continues at step 196 wherethe DST client module retrieves the task corresponding to the partialresults. For example, the partial results include header informationthat identifies the requesting entity, which correlates to the requestedtask.

The method continues at step 198 where the DST client module determinesresult processing information based on the task. For example, if thetask were to identify a particular word or phrase within the data, theresult processing information would indicate to aggregate the partialresults for the corresponding portions of the data to produce the finalresult. As another example, if the task were to count the occurrences ofa particular word or phrase within the data, results of processing theinformation would indicate to add the partial results to produce thefinal results. The method continues at step 200 where the DST clientmodule processes the partial results in accordance with the resultprocessing information to produce the final result or results.

FIG. 15 is a diagram of an example of de-grouping selection processingof an inbound distributed storage and task (DST) processing section of aDST client module. In general, this is an inverse process of thegrouping module of the outbound DST processing section of FIG. 9.Accordingly, for each data partition (e.g., partition #1), thede-grouping module retrieves the corresponding slice grouping from theDST execution units (EU) (e.g., DST 1-5).

As shown, DST execution unit #1 provides a first slice grouping, whichincludes the first encoded slices of each of the sets of encoded slices(e.g., encoded data slices of contiguous data of data blocks 1-15); DSTexecution unit #2 provides a second slice grouping, which includes thesecond encoded slices of each of the sets of encoded slices (e.g.,encoded data slices of contiguous data of data blocks 16-30); DSTexecution unit #3 provides a third slice grouping, which includes thethird encoded slices of each of the sets of encoded slices (e.g.,encoded data slices of contiguous data of data blocks 31-45); DSTexecution unit #4 provides a fourth slice grouping, which includes thefourth encoded slices of each of the sets of encoded slices (e.g., firstencoded data slices of error coding (EC) data); and DST execution unit#5 provides a fifth slice grouping, which includes the fifth encodedslices of each of the sets of encoded slices (e.g., first encoded dataslices of error coding (EC) data).

The de-grouping module de-groups the slice groupings (e.g., receivedslices 100) using a de-grouping selector 180 controlled by a controlsignal 190 as shown in the example to produce a plurality of sets ofencoded data slices (e.g., retrieved slices for a partition into sets ofslices 122). Each set corresponding to a data segment of the datapartition.

FIG. 16 is a schematic block diagram of an embodiment of a dispersedstorage (DS) error decoding module 182 of an inbound distributed storageand task (DST) processing section. The DS error decoding module 182includes an inverse per slice security processing module 202, ade-slicing module 204, an error decoding module 206, an inverse segmentsecurity module 208, a de-segmenting processing module 210, and acontrol module 186.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186, unsecures eachencoded data slice 122 based on slice de-security information receivedas control information 190 (e.g., the compliment of the slice securityinformation discussed with reference to FIG. 6) received from thecontrol module 186. The slice security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRCverification, etc.), and/or any other type of digital security. Forexample, when the inverse per slice security processing module 202 isenabled, it verifies integrity information (e.g., a CRC value) of eachencoded data slice 122, it decrypts each verified encoded data slice,and decompresses each decrypted encoded data slice to produce sliceencoded data 158. When the inverse per slice security processing module202 is not enabled, it passes the encoded data slices 122 as the slicedencoded data 158 or is bypassed such that the retrieved encoded dataslices 122 are provided as the sliced encoded data 158.

The de-slicing module 204 de-slices the sliced encoded data 158 intoencoded data segments 156 in accordance with a pillar width of the errorcorrection encoding parameters received as control information 190 fromthe control module 186. For example, if the pillar width is five, thede-slicing module 204 de-slices a set of five encoded data slices intoan encoded data segment 156. The error decoding module 206 decodes theencoded data segments 156 in accordance with error correction decodingparameters received as control information 190 from the control module186 to produce secure data segments 154. The error correction decodingparameters include identifying an error correction encoding scheme(e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction decoding parameters identify a specific errorcorrection encoding scheme, specify a pillar width of five, and specifya decode threshold of three.

The inverse segment security processing module 208, when enabled by thecontrol module 186, unsecures the secured data segments 154 based onsegment security information received as control information 190 fromthe control module 186. The segment security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRC,etc.) verification, and/or any other type of digital security. Forexample, when the inverse segment security processing module 208 isenabled, it verifies integrity information (e.g., a CRC value) of eachsecure data segment 154, it decrypts each verified secured data segment,and decompresses each decrypted secure data segment to produce a datasegment 152. When the inverse segment security processing module 208 isnot enabled, it passes the decoded data segment 154 as the data segment152 or is bypassed.

The de-segment processing module 210 receives the data segments 152 andreceives de-segmenting information as control information 190 from thecontrol module 186. The de-segmenting information indicates how thede-segment processing module 210 is to de-segment the data segments 152into a data partition 120. For example, the de-segmenting informationindicates how the rows and columns of data segments are to be rearrangedto yield the data partition 120.

FIG. 17 is a diagram of an example of de-slicing and error decodingprocessing of a dispersed error decoding module. A de-slicing module 204receives at least a decode threshold number of encoded data slices 158for each data segment in accordance with control information 190 andprovides encoded data 156. In this example, a decode threshold is three.As such, each set of encoded data slices 158 is shown to have threeencoded data slices per data segment. The de-slicing module 204 mayreceive three encoded data slices per data segment because an associateddistributed storage and task (DST) client module requested retrievingonly three encoded data slices per segment or selected three of theretrieved encoded data slices per data segment. As shown, which is basedon the unity matrix encoding previously discussed with reference to FIG.8, an encoded data slice may be a data-based encoded data slice (e.g.,DS1_d1&d2) or an error code based encoded data slice (e.g., ES3_1).

An error decoding module 206 decodes the encoded data 156 of each datasegment in accordance with the error correction decoding parameters ofcontrol information 190 to produce secured segments 154. In thisexample, data segment 1 includes 3 rows with each row being treated asone word for encoding. As such, data segment 1 includes three words:word 1 including data blocks d1 and d2, word 2 including data blocks d16and d17, and word 3 including data blocks d31 and d32. Each of datasegments 2-7 includes three words where each word includes two datablocks. Data segment 8 includes three words where each word includes asingle data block (e.g., d15, d30, and d45).

FIG. 18 is a diagram of an example of de-segment processing of aninbound distributed storage and task (DST) processing. In this example,a de-segment processing module 210 receives data segments 152 (e.g.,1-8) and rearranges the data blocks of the data segments into rows andcolumns in accordance with de-segmenting information of controlinformation 190 to produce a data partition 120. Note that the number ofrows is based on the decode threshold (e.g., 3 in this specific example)and the number of columns is based on the number and size of the datablocks.

The de-segmenting module 210 converts the rows and columns of datablocks into the data partition 120. Note that each data block may be ofthe same size as other data blocks or of a different size. In addition,the size of each data block may be a few bytes to megabytes of data.

FIG. 19 is a diagram of an example of converting slice groups into data92 within an inbound distributed storage and task (DST) processingsection. As shown, the data 92 is reconstructed from a plurality of datapartitions (1-x, where x is an integer greater than 4). Each datapartition (or chunk set of data) is decoded and re-grouped using ade-grouping and decoding function 212 and a de-partition function 214from slice groupings as previously discussed. For a given datapartition, the slice groupings (e.g., at least a decode threshold perdata segment of encoded data slices) are received from DST executionunits. From data partition to data partition, the ordering of the slicegroupings received from the DST execution units may vary as discussedwith reference to FIG. 10.

FIG. 20 is a diagram of an example of a distributed storage and/orretrieval within the distributed computing system. The distributedcomputing system includes a plurality of distributed storage and/or task(DST) processing client modules 34 (one shown) coupled to a distributedstorage and/or task processing network (DSTN) module, or multiple DSTNmodules, via a network 24. The DST client module 34 includes an outboundDST processing section 80 and an inbound DST processing section 82. TheDSTN module includes a plurality of DST execution units. Each DSTexecution unit includes a controller 86, memory 88, one or moredistributed task (DT) execution modules 90, and a DST client module 34.

In an example of data storage, the DST client module 34 has data 92 thatit desires to store in the DSTN module. The data 92 may be a file (e.g.,video, audio, text, graphics, etc.), a data object, a data block, anupdate to a file, an update to a data block, etc. In this instance, theoutbound DST processing module 80 converts the data 92 into encoded dataslices 216 as will be further described with reference to FIGS. 21-23.The outbound DST processing module 80 sends, via the network 24, to theDST execution units for storage as further described with reference toFIG. 24.

In an example of data retrieval, the DST client module 34 issues aretrieve request to the DST execution units for the desired data 92. Theretrieve request may address each DST executions units storing encodeddata slices of the desired data, address a decode threshold number ofDST execution units, address a read threshold number of DST executionunits, or address some other number of DST execution units. In responseto the request, each addressed DST execution unit retrieves its encodeddata slices 100 of the desired data and sends them to the inbound DSTprocessing section 82, via the network 24.

When, for each data segment, the inbound DST processing section 82receives at least a decode threshold number of encoded data slices 100,it converts the encoded data slices 100 into a data segment. The inboundDST processing section 82 aggregates the data segments to produce theretrieved data 92.

FIG. 21 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing section 80 of a DSTclient module coupled to a distributed storage and task network (DSTN)module (e.g., a plurality of DST execution units) via a network 24. Theoutbound DST processing section 80 includes a data partitioning module110, a dispersed storage (DS) error encoding module 112, a groupingselector module 114, a control module 116, and a distributed taskcontrol module 118.

In an example of operation, the data partitioning module 110 isby-passed such that data 92 is provided directly to the DS errorencoding module 112. The control module 116 coordinates the by-passingof the data partitioning module 110 by outputting a bypass 220 messageto the data partitioning module 110.

The DS error encoding module 112 receives the data 92 in a serialmanner, a parallel manner, and/or a combination thereof. The DS errorencoding module 112 DS error encodes the data in accordance with controlinformation 160 from the control module 116 to produce encoded dataslices 218. The DS error encoding includes segmenting the data 92 intodata segments, segment security processing (e.g., encryption,compression, watermarking, integrity check (e.g., CRC, etc.)), errorencoding, slicing, and/or per slice security processing (e.g.,encryption, compression, watermarking, integrity check (e.g., CRC,etc.)). The control information 160 indicates which steps of the DSerror encoding are active for the data 92 and, for active steps,indicates the parameters for the step. For example, the controlinformation 160 indicates that the error encoding is active and includeserror encoding parameters (e.g., pillar width, decode threshold, writethreshold, read threshold, type of error encoding, etc.).

The grouping selector module 114 groups the encoded slices 218 of thedata segments into pillars of slices 216. The number of pillarscorresponds to the pillar width of the DS error encoding parameters. Inthis example, the distributed task control module 118 facilitates thestorage request.

FIG. 22 is a schematic block diagram of an example of a dispersedstorage (DS) error encoding module 112 for the example of FIG. 21. TheDS error encoding module 112 includes a segment processing module 142, asegment security processing module 144, an error encoding module 146, aslicing module 148, and a per slice security processing module 150. Eachof these modules is coupled to a control module 116 to receive controlinformation 160 therefrom.

In an example of operation, the segment processing module 142 receivesdata 92 and receives segmenting information as control information 160from the control module 116. The segmenting information indicates howthe segment processing module is to segment the data. For example, thesegmenting information indicates the size of each data segment. Thesegment processing module 142 segments the data 92 into data segments152 in accordance with the segmenting information.

The segment security processing module 144, when enabled by the controlmodule 116, secures the data segments 152 based on segment securityinformation received as control information 160 from the control module116. The segment security information includes data compression,encryption, watermarking, integrity check (e.g., CRC, etc.), and/or anyother type of digital security. For example, when the segment securityprocessing module 144 is enabled, it compresses a data segment 152,encrypts the compressed data segment, and generates a CRC value for theencrypted data segment to produce a secure data segment. When thesegment security processing module 144 is not enabled, it passes thedata segments 152 to the error encoding module 146 or is bypassed suchthat the data segments 152 are provided to the error encoding module146.

The error encoding module 146 encodes the secure data segments inaccordance with error correction encoding parameters received as controlinformation 160 from the control module 116. The error correctionencoding parameters include identifying an error correction encodingscheme (e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction encoding parameters identify a specific errorcorrection encoding scheme, specifies a pillar width of five, andspecifies a decode threshold of three. From these parameters, the errorencoding module 146 encodes a data segment to produce an encoded datasegment.

The slicing module 148 slices the encoded data segment in accordancewith a pillar width of the error correction encoding parameters. Forexample, if the pillar width is five, the slicing module slices anencoded data segment into a set of five encoded data slices. As such,for a plurality of data segments, the slicing module 148 outputs aplurality of sets of encoded data slices as shown within encoding andslicing function 222 as described.

The per slice security processing module 150, when enabled by thecontrol module 116, secures each encoded data slice based on slicesecurity information received as control information 160 from thecontrol module 116. The slice security information includes datacompression, encryption, watermarking, integrity check (e.g., CRC,etc.), and/or any other type of digital security. For example, when theper slice security processing module 150 is enabled, it may compress anencoded data slice, encrypt the compressed encoded data slice, andgenerate a CRC value for the encrypted encoded data slice to produce asecure encoded data slice tweaking. When the per slice securityprocessing module 150 is not enabled, it passes the encoded data slicesor is bypassed such that the encoded data slices 218 are the output ofthe DS error encoding module 112.

FIG. 23 is a diagram of an example of converting data 92 into pillarslice groups utilizing encoding, slicing and pillar grouping function224 for storage in memory of a distributed storage and task network(DSTN) module. As previously discussed the data 92 is encoded and slicedinto a plurality of sets of encoded data slices; one set per datasegment. The grouping selector module organizes the sets of encoded dataslices into pillars of data slices. In this example, the DS errorencoding parameters include a pillar width of 5 and a decode thresholdof 3. As such, for each data segment, 5 encoded data slices are created.

The grouping selector module takes the first encoded data slice of eachof the sets and forms a first pillar, which may be sent to the first DSTexecution unit. Similarly, the grouping selector module creates thesecond pillar from the second slices of the sets; the third pillar fromthe third slices of the sets; the fourth pillar from the fourth slicesof the sets; and the fifth pillar from the fifth slices of the set.

FIG. 24 is a schematic block diagram of an embodiment of a distributedstorage and/or task (DST) execution unit that includes an interface 169,a controller 86, memory 88, one or more distributed task (DT) executionmodules 90, and a DST client module 34. A computing core 26 may beutilized to implement the one or more DT execution modules 90 and theDST client module 34. The memory 88 is of sufficient size to store asignificant number of encoded data slices (e.g., thousands of slices tohundreds-of-millions of slices) and may include one or more hard drivesand/or one or more solid-state memory devices (e.g., flash memory, DRAM,etc.).

In an example of storing a pillar of slices 216, the DST execution unitreceives, via interface 169, a pillar of slices 216 (e.g., pillar #1slices). The memory 88 stores the encoded data slices 216 of the pillarof slices in accordance with memory control information 174 it receivesfrom the controller 86. The controller 86 (e.g., a processing module, aCPU, etc.) generates the memory control information 174 based ondistributed storage information (e.g., user information (e.g., user ID,distributed storage permissions, data access permission, etc.), vaultinformation (e.g., virtual memory assigned to user, user group, etc.),etc.). Similarly, when retrieving slices, the DST execution unitreceives, via interface 169, a slice retrieval request. The memory 88retrieves the slice in accordance with memory control information 174 itreceives from the controller 86. The memory 88 outputs the slice 100,via the interface 169, to a requesting entity.

FIG. 25 is a schematic block diagram of an example of operation of aninbound distributed storage and/or task (DST) processing section 82 forretrieving dispersed error encoded data 92. The inbound DST processingsection 82 includes a de-grouping module 180, a dispersed storage (DS)error decoding module 182, a data de-partitioning module 184, a controlmodule 186, and a distributed task control module 188. Note that thecontrol module 186 and/or the distributed task control module 188 may beseparate modules from corresponding ones of an outbound DST processingsection or may be the same modules.

In an example of operation, the inbound DST processing section 82 isretrieving stored data 92 from the DST execution units (i.e., the DSTNmodule). In this example, the DST execution units output encoded dataslices corresponding to data retrieval requests from the distributedtask control module 188. The de-grouping module 180 receives pillars ofslices 100 and de-groups them in accordance with control information 190from the control module 186 to produce sets of encoded data slices 218.The DS error decoding module 182 decodes, in accordance with the DSerror encoding parameters received as control information 190 from thecontrol module 186, each set of encoded data slices 218 to produce datasegments, which are aggregated into retrieved data 92. The datade-partitioning module 184 is by-passed in this operational mode via abypass signal 226 of control information 190 from the control module186.

FIG. 26 is a schematic block diagram of an embodiment of a dispersedstorage (DS) error decoding module 182 of an inbound distributed storageand task (DST) processing section. The DS error decoding module 182includes an inverse per slice security processing module 202, ade-slicing module 204, an error decoding module 206, an inverse segmentsecurity module 208, and a de-segmenting processing module 210. Thedispersed error decoding module 182 is operable to de-slice and decodeencoded slices per data segment 218 utilizing a de-slicing and decodingfunction 228 to produce a plurality of data segments that arede-segmented utilizing a de-segment function 230 to recover data 92.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186 via controlinformation 190, unsecures each encoded data slice 218 based on slicede-security information (e.g., the compliment of the slice securityinformation discussed with reference to FIG. 6) received as controlinformation 190 from the control module 186. The slice de-securityinformation includes data decompression, decryption, de-watermarking,integrity check (e.g., CRC verification, etc.), and/or any other type ofdigital security. For example, when the inverse per slice securityprocessing module 202 is enabled, it verifies integrity information(e.g., a CRC value) of each encoded data slice 218, it decrypts eachverified encoded data slice, and decompresses each decrypted encodeddata slice to produce slice encoded data. When the inverse per slicesecurity processing module 202 is not enabled, it passes the encodeddata slices 218 as the sliced encoded data or is bypassed such that theretrieved encoded data slices 218 are provided as the sliced encodeddata.

The de-slicing module 204 de-slices the sliced encoded data into encodeddata segments in accordance with a pillar width of the error correctionencoding parameters received as control information 190 from a controlmodule 186. For example, if the pillar width is five, the de-slicingmodule de-slices a set of five encoded data slices into an encoded datasegment. Alternatively, the encoded data segment may include just threeencoded data slices (e.g., when the decode threshold is 3).

The error decoding module 206 decodes the encoded data segments inaccordance with error correction decoding parameters received as controlinformation 190 from the control module 186 to produce secure datasegments. The error correction decoding parameters include identifyingan error correction encoding scheme (e.g., forward error correctionalgorithm, a Reed-Solomon based algorithm, an information dispersalalgorithm, etc.), a pillar width, a decode threshold, a read threshold,a write threshold, etc. For example, the error correction decodingparameters identify a specific error correction encoding scheme, specifya pillar width of five, and specify a decode threshold of three.

The inverse segment security processing module 208, when enabled by thecontrol module 186, unsecures the secured data segments based on segmentsecurity information received as control information 190 from thecontrol module 186. The segment security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRC,etc.) verification, and/or any other type of digital security. Forexample, when the inverse segment security processing module is enabled,it verifies integrity information (e.g., a CRC value) of each securedata segment, it decrypts each verified secured data segment, anddecompresses each decrypted secure data segment to produce a datasegment 152. When the inverse segment security processing module 208 isnot enabled, it passes the decoded data segment 152 as the data segmentor is bypassed. The de-segmenting processing module 210 aggregates thedata segments 152 into the data 92 in accordance with controlinformation 190 from the control module 186.

FIG. 27 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module that includes aplurality of distributed storage and task (DST) execution units (#1through #n, where, for example, n is an integer greater than or equal tothree). Each of the DST execution units includes a DST client module 34,a controller 86, one or more DT (distributed task) execution modules 90,and memory 88.

In this example, the DSTN module stores, in the memory of the DSTexecution units, a plurality of DS (dispersed storage) encoded data(e.g., 1 through n, where n is an integer greater than or equal to two)and stores a plurality of DS encoded task codes (e.g., 1 through k,where k is an integer greater than or equal to two). The DS encoded datamay be encoded in accordance with one or more examples described withreference to FIGS. 3-19 (e.g., organized in slice groupings) or encodedin accordance with one or more examples described with reference toFIGS. 20-26 (e.g., organized in pillar groups). The data that is encodedinto the DS encoded data may be of any size and/or of any content. Forexample, the data may be one or more digital books, a copy of acompany's emails, a large-scale Internet search, a video security file,one or more entertainment video files (e.g., television programs,movies, etc.), data files, and/or any other large amount of data (e.g.,greater than a few Terabytes).

The tasks that are encoded into the DS encoded task code may be a simplefunction (e.g., a mathematical function, a logic function, an identifyfunction, a find function, a search engine function, a replace function,etc.), a complex function (e.g., compression, human and/or computerlanguage translation, text-to-voice conversion, voice-to-textconversion, etc.), multiple simple and/or complex functions, one or morealgorithms, one or more applications, etc. The tasks may be encoded intothe DS encoded task code in accordance with one or more examplesdescribed with reference to FIGS. 3-19 (e.g., organized in slicegroupings) or encoded in accordance with one or more examples describedwith reference to FIGS. 20-26 (e.g., organized in pillar groups).

In an example of operation, a DST client module of a user device or of aDST processing unit issues a DST request to the DSTN module. The DSTrequest may include a request to retrieve stored data, or a portionthereof, may include a request to store data that is included with theDST request, may include a request to perform one or more tasks onstored data, may include a request to perform one or more tasks on dataincluded with the DST request, etc. In the cases where the DST requestincludes a request to store data or to retrieve data, the client moduleand/or the DSTN module processes the request as previously discussedwith reference to one or more of FIGS. 3-19 (e.g., slice groupings)and/or 20-26 (e.g., pillar groupings). In the case where the DST requestincludes a request to perform one or more tasks on data included withthe DST request, the DST client module and/or the DSTN module processthe DST request as previously discussed with reference to one or more ofFIGS. 3-19.

In the case where the DST request includes a request to perform one ormore tasks on stored data, the DST client module and/or the DSTN moduleprocesses the DST request as will be described with reference to one ormore of FIGS. 28-39. In general, the DST client module identifies dataand one or more tasks for the DSTN module to execute upon the identifieddata. The DST request may be for a one-time execution of the task or foran on-going execution of the task. As an example of the latter, as acompany generates daily emails, the DST request may be to daily searchnew emails for inappropriate content and, if found, record the content,the email sender(s), the email recipient(s), email routing information,notify human resources of the identified email, etc.

FIG. 28 is a schematic block diagram of an example of a distributedcomputing system performing tasks on stored data. In this example, twodistributed storage and task (DST) client modules 1-2 are shown: thefirst may be associated with a user device and the second may beassociated with a DST processing unit or a high priority user device(e.g., high priority clearance user, system administrator, etc.). EachDST client module includes a list of stored data 234 and a list of taskscodes 236. The list of stored data 234 includes one or more entries ofdata identifying information, where each entry identifies data stored inthe DSTN module 22. The data identifying information (e.g., data ID)includes one or more of a data file name, a data file directory listing,DSTN addressing information of the data, a data object identifier, etc.The list of tasks 236 includes one or more entries of task codeidentifying information, when each entry identifies task codes stored inthe DSTN module 22. The task code identifying information (e.g., taskID) includes one or more of a task file name, a task file directorylisting, DSTN addressing information of the task, another type ofidentifier to identify the task, etc.

As shown, the list of data 234 and the list of tasks 236 are eachsmaller in number of entries for the first DST client module than thecorresponding lists of the second DST client module. This may occurbecause the user device associated with the first DST client module hasfewer privileges in the distributed computing system than the deviceassociated with the second DST client module. Alternatively, this mayoccur because the user device associated with the first DST clientmodule serves fewer users than the device associated with the second DSTclient module and is restricted by the distributed computing systemaccordingly. As yet another alternative, this may occur through norestraints by the distributed computing system, it just occurred becausethe operator of the user device associated with the first DST clientmodule has selected fewer data and/or fewer tasks than the operator ofthe device associated with the second DST client module.

In an example of operation, the first DST client module selects one ormore data entries 238 and one or more tasks 240 from its respectivelists (e.g., selected data ID and selected task ID). The first DSTclient module sends its selections to a task distribution module 232.The task distribution module 232 may be within a stand-alone device ofthe distributed computing system, may be within the user device thatcontains the first DST client module, or may be within the DSTN module22.

Regardless of the task distribution module's location, it generates DSTallocation information 242 from the selected task ID 240 and theselected data ID 238. The DST allocation information 242 includes datapartitioning information, task execution information, and/orintermediate result information. The task distribution module 232 sendsthe DST allocation information 242 to the DSTN module 22. Note that oneor more examples of the DST allocation information will be discussedwith reference to one or more of FIGS. 29-39.

The DSTN module 22 interprets the DST allocation information 242 toidentify the stored DS encoded data (e.g., DS error encoded data 2) andto identify the stored DS error encoded task code (e.g., DS errorencoded task code 1). In addition, the DSTN module 22 interprets the DSTallocation information 242 to determine how the data is to bepartitioned and how the task is to be partitioned. The DSTN module 22also determines whether the selected DS error encoded data 238 needs tobe converted from pillar grouping to slice grouping. If so, the DSTNmodule 22 converts the selected DS error encoded data into slicegroupings and stores the slice grouping DS error encoded data byoverwriting the pillar grouping DS error encoded data or by storing itin a different location in the memory of the DSTN module 22 (i.e., doesnot overwrite the pillar grouping DS encoded data).

The DSTN module 22 partitions the data and the task as indicated in theDST allocation information 242 and sends the portions to selected DSTexecution units of the DSTN module 22. Each of the selected DSTexecution units performs its partial task(s) on its slice groupings toproduce partial results. The DSTN module 22 collects the partial resultsfrom the selected DST execution units and provides them, as resultinformation 244, to the task distribution module. The result information244 may be the collected partial results, one or more final results asproduced by the DSTN module 22 from processing the partial results inaccordance with the DST allocation information 242, or one or moreintermediate results as produced by the DSTN module 22 from processingthe partial results in accordance with the DST allocation information242.

The task distribution module 232 receives the result information 244 andprovides one or more final results 104 therefrom to the first DST clientmodule. The final result(s) 104 may be result information 244 or aresult(s) of the task distribution module's processing of the resultinformation 244.

In concurrence with processing the selected task of the first DST clientmodule, the distributed computing system may process the selectedtask(s) of the second DST client module on the selected data(s) of thesecond DST client module. Alternatively, the distributed computingsystem may process the second DST client module's request subsequent to,or preceding, that of the first DST client module. Regardless of theordering and/or parallel processing of the DST client module requests,the second DST client module provides its selected data 238 and selectedtask 240 to a task distribution module 232. If the task distributionmodule 232 is a separate device of the distributed computing system orwithin the DSTN module, the task distribution modules 232 coupled to thefirst and second DST client modules may be the same module. The taskdistribution module 232 processes the request of the second DST clientmodule in a similar manner as it processed the request of the first DSTclient module.

FIG. 29 is a schematic block diagram of an embodiment of a taskdistribution module 232 facilitating the example of FIG. 28. The taskdistribution module 232 includes a plurality of tables it uses togenerate distributed storage and task (DST) allocation information 242for selected data and selected tasks received from a DST client module.The tables include data storage information 248, task storageinformation 250, distributed task (DT) execution module information 252,and task ⇔ sub-task mapping information 246.

The data storage information table 248 includes a data identification(ID) field 260, a data size field 262, an addressing information field264, distributed storage (DS) information 266, and may further includeother information regarding the data, how it is stored, and/or how itcan be processed. For example, DS encoded data #1 has a data ID of 1, adata size of AA (e.g., a byte size of a few Terabytes or more),addressing information of Addr_1_AA, and DS parameters of ⅗; SEG_1; andSLC_1. In this example, the addressing information may be a virtualaddress corresponding to the virtual address of the first storage word(e.g., one or more bytes) of the data and information on how tocalculate the other addresses, may be a range of virtual addresses forthe storage words of the data, physical addresses of the first storageword or the storage words of the data, may be a list of slice names ofthe encoded data slices of the data, etc. The DS parameters may includeidentity of an error encoding scheme, decode threshold/pillar width(e.g., ⅗ for the first data entry), segment security information (e.g.,SEG_1), per slice security information (e.g., SLC_1), and/or any otherinformation regarding how the data was encoded into data slices.

The task storage information table 250 includes a task identification(ID) field 268, a task size field 270, an addressing information field272, distributed storage (DS) information 274, and may further includeother information regarding the task, how it is stored, and/or how itcan be used to process data. For example, DS encoded task #2 has a taskID of 2, a task size of XY, addressing information of Addr_2_XY, and DSparameters of ⅗; SEG_2; and SLC_2. In this example, the addressinginformation may be a virtual address corresponding to the virtualaddress of the first storage word (e.g., one or more bytes) of the taskand information on how to calculate the other addresses, may be a rangeof virtual addresses for the storage words of the task, physicaladdresses of the first storage word or the storage words of the task,may be a list of slices names of the encoded slices of the task code,etc. The DS parameters may include identity of an error encoding scheme,decode threshold/pillar width (e.g., ⅗ for the first data entry),segment security information (e.g., SEG_2), per slice securityinformation (e.g., SLC_2), and/or any other information regarding howthe task was encoded into encoded task slices. Note that the segmentand/or the per-slice security information include a type of encryption(if enabled), a type of compression (if enabled), watermarkinginformation (if enabled), and/or an integrity check scheme (if enabled).

The task ⇔ sub-task mapping information table 246 includes a task field256 and a sub-task field 258. The task field 256 identifies a taskstored in the memory of a distributed storage and task network (DSTN)module and the corresponding sub-task fields 258 indicates whether thetask includes sub-tasks and, if so, how many and if any of the sub-tasksare ordered. In this example, the task ⇔ sub-task mapping informationtable 246 includes an entry for each task stored in memory of the DSTNmodule (e.g., task 1 through task k). In particular, this exampleindicates that task 1 includes 7 sub-tasks; task 2 does not includesub-tasks, and task k includes r number of sub-tasks (where r is aninteger greater than or equal to two).

The DT execution module table 252 includes a DST execution unit ID field276, a DT execution module ID field 278, and a DT execution modulecapabilities field 280. The DST execution unit ID field 276 includes theidentity of DST units in the DSTN module. The DT execution module IDfield 278 includes the identity of each DT execution unit in each DSTunit. For example, DST unit 1 includes three DT executions modules(e.g., 1_1, 1_2, and 1_3). The DT execution capabilities field 280includes identity of the capabilities of the corresponding DT executionunit. For example, DT execution module 1_1 includes capabilities X,where X includes one or more of MIPS capabilities, processing resources(e.g., quantity and capability of microprocessors, CPUs, digital signalprocessors, co-processor, microcontrollers, arithmetic logic circuitry,and/or any other analog and/or digital processing circuitry),availability of the processing resources, memory information (e.g.,type, size, availability, etc.), and/or any information germane toexecuting one or more tasks.

From these tables, the task distribution module 232 generates the DSTallocation information 242 to indicate where the data is stored, how topartition the data, where the task is stored, how to partition the task,which DT execution units should perform which partial task on which datapartitions, where and how intermediate results are to be stored, etc. Ifmultiple tasks are being performed on the same data or different data,the task distribution module factors such information into itsgeneration of the DST allocation information.

FIG. 30 is a diagram of a specific example of a distributed computingsystem performing tasks on stored data as a task flow 318. In thisexample, selected data 92 is data 2 and selected tasks are tasks 1, 2,and 3. Task 1 corresponds to analyzing translation of data from onelanguage to another (e.g., human language or computer language); task 2corresponds to finding specific words and/or phrases in the data; andtask 3 corresponds to finding specific translated words and/or phrasesin translated data.

In this example, task 1 includes 7 sub-tasks: task 1_1—identifynon-words (non-ordered); task 1_2—identify unique words (non-ordered);task 1_3—translate (non-ordered); task 1_4—translate back (ordered aftertask 1_3); task 1_5—compare to ID errors (ordered after task 1-4); task1_6—determine non-word translation errors (ordered after task 1_5 and1_1); and task 1_7—determine correct translations (ordered after 1_5 and1_2). The sub-task further indicates whether they are an ordered task(i.e., are dependent on the outcome of another task) or non-order (i.e.,are independent of the outcome of another task). Task 2 does not includesub-tasks and task 3 includes two sub-tasks: task 3_1 translate; andtask 3_2 find specific word or phrase in translated data.

In general, the three tasks collectively are selected to analyze datafor translation accuracies, translation errors, translation anomalies,occurrence of specific words or phrases in the data, and occurrence ofspecific words or phrases on the translated data. Graphically, the data92 is translated 306 into translated data 282; is analyzed for specificwords and/or phrases 300 to produce a list of specific words and/orphrases 286; is analyzed for non-words 302 (e.g., not in a referencedictionary) to produce a list of non-words 290; and is analyzed forunique words 316 included in the data 92 (i.e., how many different wordsare included in the data) to produce a list of unique words 298. Each ofthese tasks is independent of each other and can therefore be processedin parallel if desired.

The translated data 282 is analyzed (e.g., sub-task 3_2) for specifictranslated words and/or phrases 304 to produce a list of specifictranslated words and/or phrases 288. The translated data 282 istranslated back 308 (e.g., sub-task 1_4) into the language of theoriginal data to produce re-translated data 284. These two tasks aredependent on the translate task (e.g., task 1_3) and thus must beordered after the translation task, which may be in a pipelined orderingor a serial ordering. The re-translated data 284 is then compared 310with the original data 92 to find words and/or phrases that did nottranslate (one way and/or the other) properly to produce a list ofincorrectly translated words 294. As such, the comparing task (e.g.,sub-task 1_5) 310 is ordered after the translation 306 andre-translation tasks 308 (e.g., sub-tasks 1_3 and 1_4).

The list of words incorrectly translated 294 is compared 312 to the listof non-words 290 to identify words that were not properly translatedbecause the words are non-words to produce a list of errors due tonon-words 292. In addition, the list of words incorrectly translated 294is compared 314 to the list of unique words 298 to identify unique wordsthat were properly translated to produce a list of correctly translatedwords 296. The comparison may also identify unique words that were notproperly translated to produce a list of unique words that were notproperly translated. Note that each list of words (e.g., specific wordsand/or phrases, non-words, unique words, translated words and/orphrases, etc.,) may include the word and/or phrase, how many times it isused, where in the data it is used, and/or any other informationrequested regarding a word and/or phrase.

FIG. 31 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing data and taskcodes for the example of FIG. 30. As shown, DS encoded data 2 is storedas encoded data slices across the memory (e.g., stored in memories 88)of DST execution units 1-5; the DS encoded task code 1 (of task 1) andDS encoded task 3 are stored as encoded task slices across the memory ofDST execution units 1-5; and DS encoded task code 2 (of task 2) isstored as encoded task slices across the memory of DST execution units3-7. As indicated in the data storage information table and the taskstorage information table of FIG. 29, the respective data/task has DSparameters of ⅗ for their decode threshold/pillar width; hence spanningthe memory of five DST execution units.

FIG. 32 is a diagram of an example of distributed storage and task (DST)allocation information 242 for the example of FIG. 30. The DSTallocation information 242 includes data partitioning information 320,task execution information 322, and intermediate result information 324.The data partitioning information 320 includes the data identifier (ID),the number of partitions to split the data into, address information foreach data partition, and whether the DS encoded data has to betransformed from pillar grouping to slice grouping. The task executioninformation 322 includes tabular information having a taskidentification field 326, a task ordering field 328, a data partitionfield ID 330, and a set of DT execution modules 332 to use for thedistributed task processing per data partition. The intermediate resultinformation 324 includes tabular information having a name ID field 334,an ID of the DST execution unit assigned to process the correspondingintermediate result 336, a scratch pad storage field 338, and anintermediate result storage field 340.

Continuing with the example of FIG. 30, where tasks 1-3 are to bedistributedly performed on data 2, the data partitioning informationincludes the ID of data 2. In addition, the task distribution moduledetermines whether the DS encoded data 2 is in the proper format fordistributed computing (e.g., was stored as slice groupings). If not, thetask distribution module indicates that the DS encoded data 2 formatneeds to be changed from the pillar grouping format to the slicegrouping format, which will be done by the DSTN module. In addition, thetask distribution module determines the number of partitions to dividethe data into (e.g., 2_1 through 2_z) and addressing information foreach partition.

The task distribution module generates an entry in the task executioninformation section for each sub-task to be performed. For example, task1_1 (e.g., identify non-words on the data) has no task ordering (i.e.,is independent of the results of other sub-tasks), is to be performed ondata partitions 2_1 through 2_z by DT execution modules 1_1, 2_1, 3_1,4_1, and 5_1. For instance, DT execution modules 1_1, 2_1, 3_1, 4_1, and5_1 search for non-words in data partitions 2_1 through 2_z to producetask 1_1 intermediate results (R1-1, which is a list of non-words). Task1_2 (e.g., identify unique words) has similar task execution informationas task 1_1 to produce task 1_2 intermediate results (R1-2, which is thelist of unique words).

Task 1_3 (e.g., translate) includes task execution information as beingnon-ordered (i.e., is independent), having DT execution modules 1_1,2_1, 3_1, 4_1, and 5_1 translate data partitions 2_1 through 2_4 andhaving DT execution modules 1_2, 2_2, 3_2, 4_2, and 5_2 translate datapartitions 2_5 through 2_z to produce task 1_3 intermediate results(R1-3, which is the translated data). In this example, the datapartitions are grouped, where different sets of DT execution modulesperform a distributed sub-task (or task) on each data partition group,which allows for further parallel processing.

Task 1_4 (e.g., translate back) is ordered after task 1_3 and is to beexecuted on task 1 3's intermediate result (e.g., R1-3_1) (e.g., thetranslated data). DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1 areallocated to translate back task 1_3 intermediate result partitionsR1-3_1 through R1-3_4 and DT execution modules 1_2, 2_2, 6_1, 7_1, and7_2 are allocated to translate back task 1_3 intermediate resultpartitions R1-3_5 through R1-3 z to produce task 1-4 intermediateresults (R1-4, which is the translated back data).

Task 1_5 (e.g., compare data and translated data to identify translationerrors) is ordered after task 1_4 and is to be executed on task 1_4'sintermediate results (R4-1) and on the data. DT execution modules 1_1,2_1, 3_1, 4_1, and 5_1 are allocated to compare the data partitions (2_1through 2_z) with partitions of task 1-4 intermediate results partitionsR1-4_1 through R1-4_z to produce task 1_5 intermediate results (R1-5,which is the list words translated incorrectly).

Task 1_6 (e.g., determine non-word translation errors) is ordered aftertasks 1_1 and 1_5 and is to be executed on tasks 1_1's and 1_5'sintermediate results (R1-1 and R1-5). DT execution modules 1_1, 2_1,3_1, 4_1, and 5_1 are allocated to compare the partitions of task 1_1intermediate results (R1-1_1 through R1-1_z) with partitions of task 1-5intermediate results partitions (R1-5_1 through R1-5_z) to produce task1_6 intermediate results (R1-6, which is the list translation errors dueto non-words).

Task 1_7 (e.g., determine words correctly translated) is ordered aftertasks 1_2 and 1_5 and is to be executed on tasks 1_2's and 1_5'sintermediate results (R1-1 and R1-5). DT execution modules 1_2, 2_2,3_2, 4_2, and 5_2 are allocated to compare the partitions of task 1_2intermediate results (R1-2_1 through R1-2_z) with partitions of task 1-5intermediate results partitions (R1-5_1 through R1-5_z) to produce task1_7 intermediate results (R1-7, which is the list of correctlytranslated words).

Task 2 (e.g., find specific words and/or phrases) has no task ordering(i.e., is independent of the results of other sub-tasks), is to beperformed on data partitions 2_1 through 2_z by DT execution modules3_1, 4_1, 5_1, 6_1, and 7_1. For instance, DT execution modules 3_1,4_1, 5_1, 6_1, and 7_1 search for specific words and/or phrases in datapartitions 2_1 through 2_z to produce task 2 intermediate results (R2,which is a list of specific words and/or phrases).

Task 3_2 (e.g., find specific translated words and/or phrases) isordered after task 1_3 (e.g., translate) is to be performed onpartitions R1-3_1 through R1-3_z by DT execution modules 1_2, 2_2, 3_2,4_2, and 5_2. For instance, DT execution modules 1_2, 2_2, 3_2, 4_2, and5_2 search for specific translated words and/or phrases in thepartitions of the translated data (R1-3_1 through R1-3_z) to producetask 3_2 intermediate results (R3-2, which is a list of specifictranslated words and/or phrases).

For each task, the intermediate result information indicates which DSTunit is responsible for overseeing execution of the task and, if needed,processing the partial results generated by the set of allocated DTexecution units. In addition, the intermediate result informationindicates a scratch pad memory for the task and where the correspondingintermediate results are to be stored. For example, for intermediateresult R1-1 (the intermediate result of task 1_1), DST unit 1 isresponsible for overseeing execution of the task 1_1 and coordinatesstorage of the intermediate result as encoded intermediate result slicesstored in memory of DST execution units 1-5. In general, the scratch padis for storing non-DS encoded intermediate results and the intermediateresult storage is for storing DS encoded intermediate results.

FIGS. 33-38 are schematic block diagrams of the distributed storage andtask network (DSTN) module performing the example of FIG. 30. In FIG.33, the DSTN module accesses the data 92 and partitions it into aplurality of partitions 1-z in accordance with distributed storage andtask network (DST) allocation information. For each data partition, theDSTN identifies a set of its DT (distributed task) execution modules 90to perform the task (e.g., identify non-words (i.e., not in a referencedictionary) within the data partition) in accordance with the DSTallocation information. From data partition to data partition, the setof DT execution modules 90 may be the same, different, or a combinationthereof (e.g., some data partitions use the same set while other datapartitions use different sets).

For the first data partition, the first set of DT execution modules(e.g., 1_1, 2_1, 3_1, 4_1, and 5_1 per the DST allocation information ofFIG. 32) executes task 1_1 to produce a first partial result 102 ofnon-words found in the first data partition. The second set of DTexecution modules (e.g., 1_1, 2_1, 3_1, 4_1, and 5_1 per the DSTallocation information of FIG. 32) executes task 1_1 to produce a secondpartial result 102 of non-words found in the second data partition. Thesets of DT execution modules (as per the DST allocation information)perform task 1_1 on the data partitions until the “z” set of DTexecution modules performs task 1_1 on the “zth” data partition toproduce a “zth” partial result 102 of non-words found in the “zth” datapartition.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results toproduce the first intermediate result (R1-1), which is a list ofnon-words found in the data. For instance, each set of DT executionmodules 90 stores its respective partial result in the scratchpad memoryof DST execution unit 1 (which is identified in the DST allocation ormay be determined by DST execution unit 1). A processing module of DSTexecution 1 is engaged to aggregate the first through “zth” partialresults to produce the first intermediate result (e.g., R1_1). Theprocessing module stores the first intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the first intermediate result (e.g., the list ofnon-words). To begin the encoding, the DST client module determineswhether the list of non-words is of a sufficient size to partition(e.g., greater than a Terabyte). If yes, it partitions the firstintermediate result (R1-1) into a plurality of partitions (e.g., R1-1_1through R1-1_m). If the first intermediate result is not of sufficientsize to partition, it is not partitioned.

For each partition of the first intermediate result, or for the firstintermediate result, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes ⅗decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-5).

In FIG. 34, the DSTN module is performing task 1_2 (e.g., find uniquewords) on the data 92. To begin, the DSTN module accesses the data 92and partitions it into a plurality of partitions 1-z in accordance withthe DST allocation information or it may use the data partitions of task1_1 if the partitioning is the same. For each data partition, the DSTNidentifies a set of its DT execution modules to perform task 1_2 inaccordance with the DST allocation information. From data partition todata partition, the set of DT execution modules may be the same,different, or a combination thereof. For the data partitions, theallocated set of DT execution modules executes task 1_2 to produce apartial results (e.g., 1^(st) through “zth”) of unique words found inthe data partitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results102 of task 1_2 to produce the second intermediate result (R1-2), whichis a list of unique words found in the data 92. The processing module ofDST execution 1 is engaged to aggregate the first through “zth” partialresults of unique words to produce the second intermediate result. Theprocessing module stores the second intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the second intermediate result (e.g., the list ofnon-words). To begin the encoding, the DST client module determineswhether the list of unique words is of a sufficient size to partition(e.g., greater than a Terabyte). If yes, it partitions the secondintermediate result (R1-2) into a plurality of partitions (e.g., R1-2_1through R1-2_m). If the second intermediate result is not of sufficientsize to partition, it is not partitioned.

For each partition of the second intermediate result, or for the secondintermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes ⅗decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-5).

In FIG. 35, the DSTN module is performing task 1_3 (e.g., translate) onthe data 92. To begin, the DSTN module accesses the data 92 andpartitions it into a plurality of partitions 1-z in accordance with theDST allocation information or it may use the data partitions of task 1_1if the partitioning is the same. For each data partition, the DSTNidentifies a set of its DT execution modules to perform task 1_3 inaccordance with the DST allocation information (e.g., DT executionmodules 1_1, 2_1, 3_1, 4_1, and 5_1 translate data partitions 2_1through 2_4 and DT execution modules 1_2, 2_2, 3_2, 4_2, and 5_2translate data partitions 2_5 through 2_z). For the data partitions, theallocated set of DT execution modules 90 executes task 1_3 to producepartial results 102 (e.g., 1st through “zth”) of translated data.

As indicated in the DST allocation information of FIG. 32, DST executionunit 2 is assigned to process the first through “zth” partial results oftask 1_3 to produce the third intermediate result (R1-3), which istranslated data. The processing module of DST execution 2 is engaged toaggregate the first through “zth” partial results of translated data toproduce the third intermediate result. The processing module stores thethird intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 2.

DST execution unit 2 engages its DST client module to slice groupingbased DS error encode the third intermediate result (e.g., translateddata). To begin the encoding, the DST client module partitions the thirdintermediate result (R1-3) into a plurality of partitions (e.g., R1-3_1through R1-3_y). For each partition of the third intermediate result,the DST client module uses the DS error encoding parameters of the data(e.g., DS parameters of data 2, which includes ⅗ decode threshold/pillarwidth ratio) to produce slice groupings. The slice groupings are storedin the intermediate result memory (e.g., allocated memory in thememories of DST execution units 2-6 per the DST allocation information).

As is further shown in FIG. 35, the DSTN module is performing task 1_4(e.g., retranslate) on the translated data of the third intermediateresult. To begin, the DSTN module accesses the translated data (from thescratchpad memory or from the intermediate result memory and decodes it)and partitions it into a plurality of partitions in accordance with theDST allocation information. For each partition of the third intermediateresult, the DSTN identifies a set of its DT execution modules 90 toperform task 1_4 in accordance with the DST allocation information(e.g., DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1 are allocated totranslate back partitions R1-3_1 through R1-3_4 and DT execution modules1_2, 2_2, 6_1, 7_1, and 7_2 are allocated to translate back partitionsR1-3_5 through R1-3_z). For the partitions, the allocated set of DTexecution modules executes task 1_4 to produce partial results 102(e.g., 1^(st) through “zth”) of re-translated data.

As indicated in the DST allocation information of FIG. 32, DST executionunit 3 is assigned to process the first through “zth” partial results oftask 1_4 to produce the fourth intermediate result (R1-4), which isretranslated data. The processing module of DST execution 3 is engagedto aggregate the first through “zth” partial results of retranslateddata to produce the fourth intermediate result. The processing modulestores the fourth intermediate result as non-DS error encoded data inthe scratchpad memory or in another section of memory of DST executionunit 3.

DST execution unit 3 engages its DST client module to slice groupingbased DS error encode the fourth intermediate result (e.g., retranslateddata). To begin the encoding, the DST client module partitions thefourth intermediate result (R1-4) into a plurality of partitions (e.g.,R1-4_1 through R1-4_z). For each partition of the fourth intermediateresult, the DST client module uses the DS error encoding parameters ofthe data (e.g., DS parameters of data 2, which includes ⅗ decodethreshold/pillar width ratio) to produce slice groupings. The slicegroupings are stored in the intermediate result memory (e.g., allocatedmemory in the memories of DST execution units 3-7 per the DST allocationinformation).

In FIG. 36, a distributed storage and task network (DSTN) module isperforming task 1_5 (e.g., compare) on data 92 and retranslated data ofFIG. 35. To begin, the DSTN module accesses the data 92 and partitionsit into a plurality of partitions in accordance with the DST allocationinformation or it may use the data partitions of task 1_1 if thepartitioning is the same. The DSTN module also accesses the retranslateddata from the scratchpad memory, or from the intermediate result memoryand decodes it, and partitions it into a plurality of partitions inaccordance with the DST allocation information. The number of partitionsof the retranslated data corresponds to the number of partitions of thedata.

For each pair of partitions (e.g., data partition 1 and retranslateddata partition 1), the DSTN identifies a set of its DT execution modules90 to perform task 1_5 in accordance with the DST allocation information(e.g., DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1). For each pairof partitions, the allocated set of DT execution modules executes task1_5 to produce partial results 102 (e.g., 1^(st) through “zth”) of alist of incorrectly translated words and/or phrases.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results oftask 1_5 to produce the fifth intermediate result (R1-5), which is thelist of incorrectly translated words and/or phrases. In particular, theprocessing module of DST execution 1 is engaged to aggregate the firstthrough “zth” partial results of the list of incorrectly translatedwords and/or phrases to produce the fifth intermediate result. Theprocessing module stores the fifth intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the fifth intermediate result. To begin theencoding, the DST client module partitions the fifth intermediate result(R1-5) into a plurality of partitions (e.g., R1-5_1 through R1-5_z). Foreach partition of the fifth intermediate result, the DST client moduleuses the DS error encoding parameters of the data (e.g., DS parametersof data 2, which includes ⅗ decode threshold/pillar width ratio) toproduce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 1-5 per the DST allocation information).

As is further shown in FIG. 36, the DSTN module is performing task 1_6(e.g., translation errors due to non-words) on the list of incorrectlytranslated words and/or phrases (e.g., the fifth intermediate resultR1-5) and the list of non-words (e.g., the first intermediate resultR1-1). To begin, the DSTN module accesses the lists and partitions theminto a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-1_1 and partitionR1-5_1), the DSTN identifies a set of its DT execution modules 90 toperform task 1_6 in accordance with the DST allocation information(e.g., DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1). For each pairof partitions, the allocated set of DT execution modules executes task1_6 to produce partial results 102 (e.g., 1^(st) through “zth”) of alist of incorrectly translated words and/or phrases due to non-words.

As indicated in the DST allocation information of FIG. 32, DST executionunit 2 is assigned to process the first through “zth” partial results oftask 1_6 to produce the sixth intermediate result (R1-6), which is thelist of incorrectly translated words and/or phrases due to non-words. Inparticular, the processing module of DST execution 2 is engaged toaggregate the first through “zth” partial results of the list ofincorrectly translated words and/or phrases due to non-words to producethe sixth intermediate result. The processing module stores the sixthintermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 2.

DST execution unit 2 engages its DST client module to slice groupingbased DS error encode the sixth intermediate result. To begin theencoding, the DST client module partitions the sixth intermediate result(R1-6) into a plurality of partitions (e.g., R1-6_1 through R1-6_z). Foreach partition of the sixth intermediate result, the DST client moduleuses the DS error encoding parameters of the data (e.g., DS parametersof data 2, which includes ⅗ decode threshold/pillar width ratio) toproduce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 2-6 per the DST allocation information).

As is still further shown in FIG. 36, the DSTN module is performing task1_7 (e.g., correctly translated words and/or phrases) on the list ofincorrectly translated words and/or phrases (e.g., the fifthintermediate result R1-5) and the list of unique words (e.g., the secondintermediate result R1-2). To begin, the DSTN module accesses the listsand partitions them into a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-2_1 and partitionR1-5_1), the DSTN identifies a set of its DT execution modules 90 toperform task 1_7 in accordance with the DST allocation information(e.g., DT execution modules 1_2, 2_2, 3_2, 4_2, and 5_2). For each pairof partitions, the allocated set of DT execution modules executes task1_7 to produce partial results 102 (e.g., 1^(st) through “zth”) of alist of correctly translated words and/or phrases.

As indicated in the DST allocation information of FIG. 32, DST executionunit 3 is assigned to process the first through “zth” partial results oftask 1_7 to produce the seventh intermediate result (R1-7), which is thelist of correctly translated words and/or phrases. In particular, theprocessing module of DST execution 3 is engaged to aggregate the firstthrough “zth” partial results of the list of correctly translated wordsand/or phrases to produce the seventh intermediate result. Theprocessing module stores the seventh intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 3.

DST execution unit 3 engages its DST client module to slice groupingbased DS error encode the seventh intermediate result. To begin theencoding, the DST client module partitions the seventh intermediateresult (R1-7) into a plurality of partitions (e.g., R1-7_1 throughR1-7_z). For each partition of the seventh intermediate result, the DSTclient module uses the DS error encoding parameters of the data (e.g.,DS parameters of data 2, which includes ⅗ decode threshold/pillar widthratio) to produce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 3-7 per the DST allocation information).

In FIG. 37, the distributed storage and task network (DSTN) module isperforming task 2 (e.g., find specific words and/or phrases) on the data92. To begin, the DSTN module accesses the data and partitions it into aplurality of partitions 1-z in accordance with the DST allocationinformation or it may use the data partitions of task 1_1 if thepartitioning is the same. For each data partition, the DSTN identifies aset of its DT execution modules 90 to perform task 2 in accordance withthe DST allocation information. From data partition to data partition,the set of DT execution modules may be the same, different, or acombination thereof. For the data partitions, the allocated set of DTexecution modules executes task 2 to produce partial results 102 (e.g.,1^(st) through “zth”) of specific words and/or phrases found in the datapartitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 7 is assigned to process the first through “zth” partial results oftask 2 to produce task 2 intermediate result (R2), which is a list ofspecific words and/or phrases found in the data. The processing moduleof DST execution 7 is engaged to aggregate the first through “zth”partial results of specific words and/or phrases to produce the task 2intermediate result. The processing module stores the task 2intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 7.

DST execution unit 7 engages its DST client module to slice groupingbased DS error encode the task 2 intermediate result. To begin theencoding, the DST client module determines whether the list of specificwords and/or phrases is of a sufficient size to partition (e.g., greaterthan a Terabyte). If yes, it partitions the task 2 intermediate result(R2) into a plurality of partitions (e.g., R2_1 through R2_m). If thetask 2 intermediate result is not of sufficient size to partition, it isnot partitioned.

For each partition of the task 2 intermediate result, or for the task 2intermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes ⅗decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-4, and 7).

In FIG. 38, the distributed storage and task network (DSTN) module isperforming task 3 (e.g., find specific translated words and/or phrases)on the translated data (R1-3). To begin, the DSTN module accesses thetranslated data (from the scratchpad memory or from the intermediateresult memory and decodes it) and partitions it into a plurality ofpartitions in accordance with the DST allocation information. For eachpartition, the DSTN identifies a set of its DT execution modules toperform task 3 in accordance with the DST allocation information. Frompartition to partition, the set of DT execution modules may be the same,different, or a combination thereof. For the partitions, the allocatedset of DT execution modules 90 executes task 3 to produce partialresults 102 (e.g., 1^(st) through “zth”) of specific translated wordsand/or phrases found in the data partitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 5 is assigned to process the first through “zth” partial results oftask 3 to produce task 3 intermediate result (R3), which is a list ofspecific translated words and/or phrases found in the translated data.In particular, the processing module of DST execution 5 is engaged toaggregate the first through “zth” partial results of specific translatedwords and/or phrases to produce the task 3 intermediate result. Theprocessing module stores the task 3 intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 7.

DST execution unit 5 engages its DST client module to slice groupingbased DS error encode the task 3 intermediate result. To begin theencoding, the DST client module determines whether the list of specifictranslated words and/or phrases is of a sufficient size to partition(e.g., greater than a Terabyte). If yes, it partitions the task 3intermediate result (R3) into a plurality of partitions (e.g., R3_1through R3_m). If the task 3 intermediate result is not of sufficientsize to partition, it is not partitioned.

For each partition of the task 3 intermediate result, or for the task 3intermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes ⅗decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-4, 5, and 7).

FIG. 39 is a diagram of an example of combining result information intofinal results 104 for the example of FIG. 30. In this example, theresult information includes the list of specific words and/or phrasesfound in the data (task 2 intermediate result), the list of specifictranslated words and/or phrases found in the data (task 3 intermediateresult), the list of non-words found in the data (task 1 firstintermediate result R1-1), the list of unique words found in the data(task 1 second intermediate result R1-2), the list of translation errorsdue to non-words (task 1 sixth intermediate result R1-6), and the listof correctly translated words and/or phrases (task 1 seventhintermediate result R1-7). The task distribution module provides theresult information to the requesting DST client module as the results104.

FIGS. 40A-B are schematic block diagrams of an embodiment of a dispersedstorage network (DSN) illustrating an example of executing tasks. TheDSN includes distributed storage and task (DST) client modules 1-M, thenetwork 24 of FIG. 1, and a DST execution unit set 350. Each DST clientmodule may be implemented utilizing the DST client module 34 of FIG. 1.Each DST client module includes the outbound dispersed storage (DS)processing module 80 and the inbound DS processing module 82 of FIG. 3.The outbound DS processing module 80 includes the distributed taskcontrol module 118 of FIG. 4 and the DS error encoding 112 of FIG. 4.The inbound DS processing module 82 includes the distributed taskcontrol module 188 and the DS error decoding 182 of FIG. 13. The DSTexecution unit set 350 includes a set of DST execution units 1-n. EachDST execution unit may be implemented using the DST execution unit 36 ofFIG. 1.

FIG. 40A illustrates initial steps of the executing of the tasks. In anexample of operation, the distributed task control module 118 of the DSTclient module 1 obtains a task 352. The obtaining includes at least oneof receiving and generating. The task 352 includes one or more of a taskdescription, a task identifier, subtask descriptions, and subtaskidentifiers. The task description may include one or more of read data,process data, perform a selection, perform an identification, writedata, retrieve data, manipulate data, store data, etc. The subtaskdescription may include one or more of identifying a storage address,generate a retrieval request, send a retrieval request, receiveretrieval responses, decode the retrieval responses, etc., when anassociated task of the subtask includes the read data task.

Having obtained the task 352, the distributed task control module 118obtains a task object 354. The obtaining includes retrieving an existingtask object, retrieving an entry of a dispersed hierarchical index, andgenerating a new task object as the obtained task object. Havingobtained the task object 354, the distributed task control module 118generates a task entry 356-358 etc., for the task object 354 based onthe task. Each task object 354 includes one or more task entries. Eachtask entry 356 etc., includes a task, a rule set, and status. The ruleset includes one or more of a precondition for task execution, acondition to maintain task execution, and one or more conditionparameters. For example, the rule set indicates to execute the taskafter a certain time frame has elapsed. The status may include anexecution owner identifier (ID) and a state of processing of the task.The state of the processing of the task includes at least one of apending execution state, an active execution state, and an executioncomplete state.

The generating of the task entry includes generating the task entry inaccordance with a task entry generation approach based on the task. As aspecific example of generating the task entry, the distributed taskcontrol module 118 generates the task entry to indicate task 203, ruleset 2, and the status to include the pending execution state (e.g.,state 0) when the task entry generation approach indicates to utilizerule set 2 for task 203. The distributed task control module 118 addsthe generated task entry 356, 358, etc., to the obtained task object 354to produce the task object 354 for further processing.

The DS error encoding 112 dispersed storage error encodes the taskobject 354 to produce task slices 360, where the task slices 360includes a set of task slices 1-n. Having produced the task slices 360,the outbound DS processing module 80 sends, via the network 24, the taskslices 360 to the DST execution unit set 350 such that each of the DSTexecution units 1-n store a corresponding task slice of the set of taskslices 1-n. For example, the task slices are stored as a new object inthe DST execution unit set. As another example, the task slices 360 arestored as a new entry within an index node of a dispersed hierarchicalindex structure stored in the DST execution unit set 350. Having storedthe task slices 360, the task has been queued.

FIG. 40B illustrates further steps of the executing of the tasks. Havingone or more tasks queued in the DST execution unit set 350, the inboundDS processing module 82 of DST client module 2 retrieves at least adecode threshold number of task slices 360 from the DST execution unitset 350. For example, the DS error decoding 182 issues a read thresholdnumber of read slice requests to a read threshold number of the DSTexecution units 1-n to recover at least one of the data objectassociated with the task object and the index node of the dispersedhierarchical index that includes the index node entry associated withthe task object. Having issued the read threshold number of read slicerequests, the DS error decoding 182 receives at least a decode thresholdnumber of read slice responses that includes the at least a decodethreshold number of task slices 360.

Having received the at least a decode threshold number of task slices360, the DS error decoding 182 dispersed storage error decodes the atleast a decode threshold number of task slices 360 to produce arecovered task object 362. The distributed task control module 188determines whether to execute a task of the recovered task object. Forexample, the distributed task control module 188 selects a task entry ofthe recovered task object 362, interprets the status to determine thatthe task is pending execution, analyzes the rule set to determine thatthe rule set has been satisfied begin execution, and that the DST clientmodule 2 has sufficient available resources to execute the task of thetask entry.

When the distributed task control module 188 determines to execute thetask, the distributed task control module 188 initiates obtainingownership of the task. For example, the distributed task control module118 updates the status of the task entry to indicate ownership by DSTclient module 2 to produce an updated task object 370. The DS errorencoding 112 dispersed storage error encodes the updated task object 370to produce a set of updated task slices 376. The outbound DS processingmodule 80 issues, via the network 24, a set of write slice requests thatincludes the set of updated task slices 376 to the DST execution units1-n for storage of the set of updated task slices 376, and receives, viathe network 24, at least a write threshold number of favorable writeslice responses confirming ownership by the DST client module 1 of thetask and storage of the updated task object in the DST execution unitset.

When receiving confirmation of ownership, the distributed task controlmodule 188 facilitates initiation of execution of the task. Theinitiation of the execution of the task includes determining whether toutilize subtasks 368. For example, the distributed task control module188 determines to utilize the subtasks when the DST client module 2 doesnot have enough resources to fully execute the task. As another example,the distributed task control module 188 determines to utilize thesubtasks when the rule set of the task entry indicates to utilizesubtasks.

When utilizing the subtasks 368, the distributed task control module 188generates one or more subtasks 368 in accordance with the rule set andbased on the task. The distributed task control module 118 furtherupdates the updated task object 370 to produce a further updated taskobject 370 where the task entry 374 of the further updated task object370 includes the subtasks. The DS error encoding 112 dispersed storageerror encodes the further updated task object to produce further updatedtask slices 376. The outbound DS processing module 80 facilitatesstorage of the further updated task slices 376 in the set of DSTexecution units 1-n. The above process may continue where yet anotherDST client module accesses the further updated task object to retrieve asubtask, obtain ownership of the subtasks, execute a selected subtaskand/or create further subtasks from the selected subtask.

FIG. 40C is a flowchart illustrating an example of executing tasks. Themethod begins or continues at step 380 where a first module (e.g., of afirst distributed storage and task (DST) client module) obtains a taskobject. For example, the first module searches a dispersed hierarchicalindex to identify an entry that includes the task object. The methodcontinues at step 382 where the first module generates a task entrybased on a task (e.g., a new task to be queued for subsequentexecution). The method continues at step 384 where the first moduleupdates the task object to include the task entry. The method continuesat step 386 where the first module facilitates storing the task objectin a dispersed storage network (DSN). For example, the first moduledispersed storage error encodes the task object to produce a set of taskslices for storage in an entry of the dispersed hierarchical index in aset of storage units of the DSN.

The method continues at step 388 where a second module (e.g., of asecond distributed storage and task (DST) client module) recovers thetask object from the DSN. For example, the second module searches thedispersed hierarchical index to identify the entry that includes thetask object. The method continues at step 390 where the second moduledetermines whether to execute the task of the task entry. For example,the processing module indicates to execute the task when status of thetask indicates that ownership no longer exists, a rule set has beensatisfied, and required resources are available.

When executing the task, the method continues at step 392 where thesecond module initiates obtaining ownership of the execution of thetask. For example, the second module updates the status of the taskentry to indicate ownership by the second module, updates the taskobject to include the updated task entry, dispersed storage errorencodes the updated task object to produce a set of updated task slices,and issues a set of write slice requests to the set of storage units ofthe DSN, where the set of write slice requests includes the set ofupdated task slices.

When ownership is confirmed, the method continues at step 394 where thesecond module facilitates initiation of the execution of the task. Thesecond module indicates that the ownership is confirmed when receivingat least a write threshold number of favorable write slice responsesfrom the set of storage units with regards to the storage of the set ofupdated task slices. As an example of execution of the task, the secondmodule determines whether to utilize subtasks. For instance, the secondmodule indicates to utilize subtasks when available resources of thesecond module compare unfavorably (e.g., not enough) to requiredresources to fulfill execution of the task. As another instance, thesecond module executes the task when the available resources of thesecond module compare favorably to the required resources to fulfill theexecution of the task.

When utilizing subtasks for the facilitation, the method continues atstep 396 where the second module generates one or more subtasks inaccordance with a subtask list and a rule set based on one or more ofthe subtask and available resources. For example, the second modulegenerates two subtasks for execution by the second module and one moresubtask for execution by another module. The method continues at step398 where the second module updates the task object to include at leastsome of the one or more subtasks. For example, the second modulegenerates a subtask entry for each subtask to be included in the taskobject. The method continues at step 400 where the second module storesthe updated task object in the set of storage units of the DSN. Forexample, the second module encodes the updated task object to produceupdated task slices and stores the updated task slices in the set ofstorage units.

FIGS. 41A, G, and H is a schematic block diagram of another embodimentof a dispersed storage network (DSN) that includes the distributedstorage and task (DST) client module 34 of FIG. 1, the network 24 ofFIG. 1, and a DST execution (EX) unit set 402. The DST client module 34includes the outbound dispersed storage (DS) processing module 80 andthe inbound DS processing module 82 of FIG. 3. The outbound DSprocessing module 80 includes the data partitioning 110 of FIG. 4 andthe DS error encoding 112 of FIG. 4. The inbound DS processing module 82includes the data de-partitioning 184 and the DS error decoding 182 ofFIG. 13. Each DST execution unit set 402 includes a set of DST EX units1-n. The set of DST EX units 1-n includes first set of DST executionunits 1-k and a second set of DST EX units k+1 through n. Each DSTexecution unit may be implemented utilizing the DST execution unit 36 ofFIG. 1.

The DSN functions to access stored data in the DSN. The accessingincludes storing data in the DST execution unit set 402 as a set ofencoded data slices utilizing a data concatenation approach. Theaccessing further includes retrieving the stored data from the DSTexecution unit set 402 in accordance with the data concatenationapproach. The data may include a plurality of small data objects, wherea size of each of a substantial number of the data objects is less thana size threshold level. Such a size threshold level may include a sizeof desired encoded data slice for storage in one of the DST executionunits. Hereafter, the plurality of small data objects may be referred tointerchangeably as a plurality of independent data objects. Theplurality of independent data objects may be associated with a commontrait. The common traits includes one or more of a size that is lessthan the size threshold level, a common subject matter, a common datatypes, a common time of arrival, a common data owner, a common date ofcreation, a common generation source, a common expected retrievingentity, etc.

FIG. 41A illustrates an example of operation of the storing of the datato produce the stored data, where the outbound DS processing module 80receives the small data objects 404 for storage. Having received theplurality small data objects 404, the outbound DS processing module 80determines whether to utilize the data concatenation approach. Thedetermining may be based on one or more of a predetermination, detectingthat at least a decode threshold number of the small data objects havebeen received, receiving a message to concatenate the independent dataobjects, where the message is one of a user input message to group dataobjects having the common trait and a system message based on dispersedstorage network conditions (e.g., the message indicating that anoverload condition may exist, and detecting that a number ofinput/output operations of the DST client module 34 is greater than aninput/output operations threshold level (e.g., inferring that theoverload condition may exist).

When using the data concatenation approach, the data partitioning 110concatenates the plurality of independent data objects 404 into aconcatenated data object 406, where the concatenating is based on aparameter of a dispersed storage error encoding function that indicatesa number of data-based encoded data slices (e.g., a decode thresholdnumber) resulting from performing the dispersed storage error encodingfunction. As a specific example, the data partitioning 110 identifiesdata objects 404 having the common trait and establishes the pluralityof independent data objects from the data objects having the commontrait. For instance, the data partitioning 110 selects a decodethreshold number (e.g., k) of small data objects 404 to produce theplurality of independent data objects for concatenation.

Having selected the plurality of independent data objects forconcatenation, the data partitioning 110 maps the independent dataobjects into “k” rows to produce the concatenated data object 406. As aspecific example of the mapping, the data partitioning 110 mapsindependent data objects into the “k” rows to produce the concatenateddata object, where the “k” rows corresponds to the number of data-basedencoded data slices resulting from performing the dispersed storageerror encoding function and where an independent data object of theplurality of independent data objects is mapped to more than one row ofthe “k” rows (e.g., an independent data object wraps from one row to anadjacent row).

As another specific example of the mapping, the data partitioning 110maps the independent data objects such that the “k” rows corresponds toa number of data-based encoded data slices (e.g., the decode thresholdnumber) resulting from performing the dispersed storage error encodingfunction and where the one or more independent data objects is mapped toa single row of the “k” rows. As a specific example of generating theconcatenated object 406 where the one or more independent data objectsare mapped to the single row, the data partitioning 110 generates theconcatenated object 406 to include small data object 1 in a first row,small data object 2 in a second row, small data object 3 in a third row,through small data object k in a “kth” row. Having mapped one small dataobject to each row, the data partitioning 110 pads the single row of the“k” rows when a combined size of the one or more independent dataobjects is less than a row size (e.g., a size of a desired encoded dataslice). For instance, the data partitioning 110 pads the first row suchthat a size of the small data object 1 plus a size of a padding 1 equalsthe row size, pads the second row such that a size of the small dataobject 2 plus a size of a padding 2 equals the row size, etc. Anotherspecific example of generating the concatenated object 406 where the oneor more independent data objects are mapped to the single row isdiscussed in greater detail with reference to FIG. 41F.

Having produced the concatenated object 406, the outbound DS processingmodule 80 performs the dispersed storage error coding function on theconcatenated data object 406 to produce the set of encoded data slicesthat includes a set of data-based encoded data slices 1-k 408 and a setof redundancy-based encoded data slices 410 (e.g., error coding slices).One or more independent data objects of the plurality of independentdata objects is recoverable from a corresponding data-based encoded dataslice of the set of encoded data slices or from a decode thresholdnumber of encoded data slices, where the decode threshold number ofencoded data slices includes one or more data-based encoded data slicesof the set of data-based encoded data slices and one or moreredundancy-based encoded data slices of the set of redundancy-basedencoded data slices.

As a specific example, the DS error encoding 112 converts theconcatenated data object 406 into a data matrix, generates a codedmatrix based on the data matrix and an encoding matrix, generates theset of data-based encoded data slices 408 (e.g., data-based encoded dataslices 1-3) from a first portion of the coded matrix that corresponds toa first portion of the encoding matrix, and generates the set ofredundancy-based encoded data slices 410 (e.g., redundancy-based encodeddata slices or error coding slices k+1 and n) from a second portion ofthe coded matrix that corresponds to a second portion of the encodingmatrix. The generating of the encoded data slices is discussed ingreater detail with reference to FIGS. 41B-E.

Having generated the set of encoded data slices, the DS error encoding112 outputs, via the network 24, the set of data-based encoded dataslices to the first set of DST execution units (e.g., DST EX units 1-k)for storage and outputs, via the network 24 the set of redundancy-basedencoded data slices to the second set of DST execution units (e.g., DSTEX units k+1 through n) for storage. For example, the DS error encoding112 sends, via the network 24, encoded data slices 1-3 to DST executionunits 1-3 for storage and sends, via the network 24, error coded dataslices 4 and 5 to DST execution units 4 and 5 for storage when k=3 andn=5.

Having output the set of encoded data slices, the outbound DS processingmodule 80 associates identifiers of the small data objects withcorresponding identifiers (e.g., slice names, source name, DSN address)of each of the set of data-based encoded data slices. For example, theoutbound DS processing module 80 updates one or more of a DSN directoryand a dispersed hierarchical index to associate received identifiers ofthe small data objects with the identifiers of the corresponding set ofdata-based encoded data slices.

FIG. 41B is a diagram illustrating an example of encoding a concatenatedobject into a plurality of data blocks D1-Dn. The set of data blocksprovides a representation of the concatenated object 406 for example,the concatenated object 406 is divided into n equal portions to formdata blocks D1-Dn. As another example, the concatenated data object 406is divided into as many portions as required when a fixed data portionsize is utilized.

FIG. 41C is a diagram illustrating an example of matrix multiplicationof an encoding matrix (E) and a data matrix (D) using a dispersedstorage error coding function to produce a coded matrix (C). Theencoding function may utilize a variety of encoding approaches tofacilitate dispersed storage error encoding of data. The encodingfunction includes, but is not limited to, at least one of Reed Solomonencoding, an information dispersal algorithm, on-line codes, forwarderror correction, erasure codes, convolution encoding, Trellis encoding,Golay, Multidimensional parity, Hamming, Bose Ray Chauduri Hocquenghem(BCH), and/or Cauchy-Reed-Solomon. In an example of a Reed Solomonencoding function, the matrix multiplication is utilized to encode adata segment or concatenated object 406 to produce a set of encoded datablocks 412 as a representation of the data segment or concatenatedobject 406. The Reed Solomon encoding function is associated with anerror coding number (e.g., pillar width, number of slices per set) and adecode threshold number. As a specific example, the encoding matrixincludes the error coding number of Y rows and the decode thresholdnumber of X columns. Accordingly, the encoding matrix includes Y rows ofX coefficients. The set of data blocks of the data segment orconcatenated object 406 is arranged into the data matrix having X rowsof Z number of data words (e.g., X*Z=number of data blocks). The datamatrix is matrix multiplied by the encoding matrix to produce the codedmatrix, which includes Y rows of Z number of encoded values (e.g.,encoded data blocks 412).

FIG. 41D is a diagram illustrating another example of matrixmultiplication of an encoding matrix (E) and a data matrix (D) using adispersed storage error coding function to produce a coded matrix (C),where a set of encoded data slices are produced from the coded matrix.In an example of operation of using a Reed Solomon encoding function,the concatenated object 406 of FIG. 41B is converted into data blocks(e.g., D1-D12) of a portion of the data matrix (e.g., any number ofbytes per block). Next, the encoding matrix is matrix multiplied by thedata matrix to produce the coded matrix, where the coded matrix includesencoded data blocks 412. As a specific example, the dispersed storageerror encoding utilizes an error coding number of five and a decodethreshold number of three. The encoding matrix (E) includes five rows ofthree coefficients (e.g., a-o). The data segment is divided into datablocks D1-12, which are arranged into the portion of the data matrix (D)having 3 rows of 4 data blocks when the number of data blocks is 12. Thenumber of rows of the data matrix matches the number of columns of theencoding matrix (e.g., the decode threshold number). The number ofcolumns of the data matrix increases as the number of data blocks of thedata segment increases. The data matrix is matrix multiplied by theencoding matrix to produce the coded matrix, which includes 5 rows of 4encoded data blocks (e.g., X11-X14, X21-X24, X31-X34, X41-X44, andX51-X54). The number of rows of the coded matrix matches the number ofrows of the encoding matrix (e.g., the error coding number). Forinstance, X11=aD1+bD5+cD9; X12=aD2+bD6+cD10; X21=dD1+eD5+fD9;X31=gD1+hD5+iD9; X34=gD4+hD8+iD12; and X54=mD4+nD8+oD12.

One or more encoded data blocks 412 from each row of the coded matrixare selected to form a corresponding encoded data slice of the set ofencoded data slices. Accordingly, an error coding number of encoded dataslices are produced from the coded matrix. For example, coded valuesX11-X14 are selected to produce an encoded data slice 1, coded valuesX21-X24 are selected to produce an encoded data slice 2, coded valuesX31-X34 are selected to produce an encoded data slice 3, coded valuesX41-X44 are selected to produce an encoded data slice 4, and codedvalues X51-X54 are selected to produce an encoded data slice 5. The datamatrix (e.g., the concatenated object 406) may be recovered (e.g., toproduce a recovered data segment) when any decode threshold number ofcorruption-free error coded data slices are available of the set oferror coded data slices. Alternatively, the recovered concatenatedobject may be produced when a decode threshold number of encoded datablocks for each column of the coded matrix are available.

FIG. 41E is a diagram illustrating another example of matrixmultiplication of an encoding matrix (E) and a data matrix (D) using adispersed storage error coding function to produce a coded matrix (C),where a decode threshold number of rows of the encoding matrix includesa unity matrix. Accordingly, matrix multiplying the encoding matrix withthe data matrix produces the coded matrix where the encoded data blocks412 include a set of encoded data slices.

The set of encoded data slices includes a set of data-based encoded dataslices 1-3 and a set of redundancy-based encoded data slices 4-5 whenthe error coding number is five (e.g., n=5) and the decode thresholdnumber is three (e.g., k=3). For example, matrix multiplying a firstportion of the encoding matrix that includes the unity matrix by thedata matrix produces a first portion of the coded matrix that includesthe set of data-based encoded data slices 1-3 and matrix multiplying asecond portion of the encoding matrix (e.g., remaining rows after theunity matrix) by the data matrix produces a second portion of the codedmatrix that includes the set of redundancy-based encoded data slices4-5. For instance, coded matrix values X11-X14 includes data blocksD1-D4 forming data-based encoded data slice 1, coded matrix valuesX21-X24 includes data blocks D5-D8 forming data-based encoded data slice2, and coded matrix values X31-X34 includes data blocks D9-D12 formingdata-based encoded data slice 3. As another instance, coded matrixvalues X41-X44 forms redundancy-based encoded data slice 4, and codedmatrix values X51-X54 forms redundancy-based encoded data slice 5.

FIG. 41F is a diagram illustrating an example of mapping data objects tothe concatenated object 406 where the independent data objects aremapped such that the “k” rows corresponds to a number of data-basedencoded data slices (e.g., the decode threshold number) resulting fromperforming the dispersed storage error encoding function and where theone or more independent data objects is mapped to a single row of the“k” rows. As a specific example of generating the concatenated object406 where the one or more independent data objects are mapped to thesingle row, the data partitioning 110 generates the concatenated object406 to include small data objects 1 and 2 in a first row, small dataobject 3 in a second row, small data object 4 in a third row, throughsmall data object k+1 in a “kth” row. Having mapped the one or moresmall data objects to each row, padding is added to each row of the “k”rows when a combined size of the one or more independent data objects isless than a row size (e.g., a size of a desired encoded data slice). Forinstance, the first row is padded such that a size of the small dataobject 1 and 2 plus a size of a padding 1 equals the row size, thesecond row is padded such that a size of the small data object 3 plus asize of a padding 2 equals the row size, etc.

FIG. 41G illustrates an example of retrieving the stored data toreproduce the data in accordance with the data concatenation approachwhere the inbound DS processing module 82 identifies an identifier of astored encoded data slice corresponding to a small data object forretrieval. For example, the inbound DS processing module 82 accesses atleast one of a DSN directory and a dispersed hierarchical index using anidentifier of the small data object for retrieval to recover theidentifier (e.g., slice name) of the corresponding stored encoded dataslice. For instance, the inbound DS processing module 82 obtains a slicename corresponding to encoded data slice 2 that includes storage ofsmall data object 2 for retrieval.

Having identified the identifier of the corresponding stored encodeddata slice, the inbound DS processing module 82 initiates retrieval ofthe stored encoded data slice. For example, the inbound DS processingmodule 82 issues a read slice request to a DST execution unitcorresponding to the identifier of the stored encoded data slice forretrieval and receives a read slice response that includes the storedencoded data slice when the stored encoded data slice is available. Forinstance, the DS error decoding 182 receives, via the network 24,encoded data slice 2 from DST execution unit 2 when the encoded dataslice 2 is available from the DST execution unit 2.

Having received the corresponding stored encoded data slice thatincludes the small data object for retrieval, the inbound DS processingmodule 82 extracts the small data object from the received correspondingstored encoded data slice. For example, the data de-partitioning 184extracts the small data object 2 from the received encoded data slice 2to produce recovered small data object 2.

FIG. 41H illustrates an example of retrieving the stored data toreproduce the data in accordance with the data concatenation approachwhere the inbound DS processing module 82 retrieves a decode thresholdnumber of encoded data slices of the set of encoded data slices. Forexample, the inbound DS processing module 82 determines that the storedencoded data slice 2 is not available from the corresponding DSTexecution unit 2 by at least one of detecting that a response timeframehas expired since issuing the read slice request, receiving no readslice response, and receiving an unfavorable read slice response (e.g.,but does not include the stored encoded data slice). Having determinedthat the stored encoded data slice is not available, the inbound DSprocessing module 82 issues a decode threshold number of read slicerequests to other DST execution units of the DST execution unit set 402,and receives at least a decode threshold number of favorable read sliceresponses that includes the decode threshold number of encoded dataslices of the set of encoded data slices. For example, the DS errordecoding 182 receives, via the network 24, the decode threshold numberof encoded data slices that includes one or more data slices 408 and oneor more error coding slices 410.

Having received the decode threshold number of encoded data slices, theDS error decoding 182 dispersed storage error decodes the receiveddecode threshold number of encoded data slices to produce a recoveredconcatenated object 414. The data de-partitioning 184 extracts theencoded data slice for retrieval from the recovered concatenated objectto produce a recovered small data object. For example, the datade-partitioning 184 extracts the encoded data slice 2 for retrieval fromthe recovered concatenated object 414 and extracts the small data object2 from the extracted encoded data slice 2.

FIG. 41I is a flowchart illustrating an example of concatenating dataobjects for storage. In particular, a method is presented for use inconjunction with one or more functions and features described inconjunction with FIGS. 1-39 and 41A-H. The method begins at step 420where a processing module of a computing device of one or more computingdevices of a dispersed storage network (DSN) receives a message toconcatenate a plurality of independent data objects, where the messageis one of a user input message to group data objects having a commontrait and a system message based on dispersed storage networkconditions.

The method continues at step 422 where the processing moduleconcatenates the plurality of independent data objects into aconcatenated data object, where the concatenating is based a parameterof a dispersed storage error encoding function that indicates a numberof data-based encoded data slices (e.g., a decode threshold number)resulting from performing the dispersed storage error encoding function.As a specific example, the processing module identifies data objectshaving the common trait and establishes the plurality of independentdata objects from the data objects having the common trait.

As another specific example of the concatenating of the plurality ofindependent data objects, the processing module maps the plurality ofindependent data objects into “k” rows to produce the concatenated dataobject, wherein the “k” rows corresponds to a number of data-basedencoded data slices resulting from performing the dispersed storageerror encoding function and wherein the one or more independent dataobjects is mapped to a single row of the “k” rows. The processing modulepads the single row of the “k” rows when a combined size of the one ormore independent data objects is less than a row size.

As yet another specific example of the concatenating the plurality ofindependent data objects, the processing module maps the plurality ofindependent data objects into “k” rows to produce the concatenated dataobject, where the “k” rows corresponds to a number of data-based encodeddata slices resulting from performing the dispersed storage errorencoding function and where an independent data object of the pluralityof independent data objects is mapped to more than one row of the “k”rows.

The method continues at step 424 where the processing module performsthe dispersed storage error encoding function on the concatenated dataobject to produce a set of data-based encoded data slices and a set ofredundancy-based encoded data slices, where one or more independent dataobjects of the plurality of independent data objects is recoverable froma corresponding data-based encoded data slice of the set of encoded dataslices or from a decode threshold number of encoded data slices. Thedecode threshold number of encoded data slices includes one or moredata-based encoded data slices of the set of data-based encoded dataslices and one or more redundancy-based encoded data slices of the setof redundancy-based encoded data slices. As a specific example, theprocessing module converts the concatenated data object into a datamatrix, generates a coded matrix based on the data matrix and anencoding matrix, generates the set of data-based encoded data slicesfrom a first portion of the coded matrix that corresponds to a firstportion of the encoding matrix, and generates the set ofredundancy-based encoded data slices from a second portion of the codedmatrix that corresponds to a second portion of the encoding matrix.

The method continues at step 426 where the processing module outputs theset of data-based encoded data slices to a first set of storage unitsfor storage. The method continues at step 428 where the processingmodule outputs the set of redundancy-based encoded data slices to asecond set of storage units for storage.

The method described above in conjunction with the processing module canalternatively be performed by other modules of the dispersed storagenetwork or by other devices. In addition, at least one memory section ofa computer readable storage medium that stores operational instructionscan, when executed by one or more processing modules of one or morecomputing devices of the dispersed storage network (DSN), cause the oneor more computing devices to perform any or all of the method stepsdescribed above.

FIGS. 42A-C are schematic block diagrams of another embodiment of adispersed storage network (DSN) illustrating an example of storing andretrieving data. The DSN includes dispersed storage and task (DST)execution unit sets 1-2, the network 24 of FIG. 1, and the DST clientmodule 34 of FIG. 1. Each DST execution unit set includes a set of DSTexecution units 1-n. Each DST execution unit may be implementedutilizing the DST execution unit 36 of FIG. 1. The DST client module 34includes the outbound dispersed storage (DS) processing module 80 andthe inbound DS processing module 82 of FIG. 3. Each DST execution unitset may be associated with attributes of the corresponding set of DSTexecution units. Such attributes include one or more of storagecapacity, storage latency, retrieval reliability, storage availability,and ingestion rate capability. Each DST execution unit set may beassociated with value ranges of the attributes with respect to the otherDST execution unit sets. For example, DST execution unit set 1 may beassociated with lower than average storage capacity and higher thanaverage ingestion rate capability while DST execution unit set 2 may beassociated with higher than average storage capacity and averageingestion rate capability.

FIG. 42A illustrates initial steps of the example of the storing of thedata to produce stored data. As a specific example, the outbound DSprocessing module 80 initiates receiving of the data 430 (e.g., a longtransfer, a data stream) for storage and tracks a cumulative size of thereceived data 430 while the data has been received. While the cumulativesize of the received data is less than a size threshold level, theoutbound DS processing module 80 facilitates storage of a portion of thereceived data 430 in the DST execution unit set 1. For example, theoutbound DS processing module 80 partitions the portion of the receiveddata to produce a data segment, dispersed storage error encodes the datasegment to produce a set of encoded data slices (e.g., slices 1-1, 1-2,through 1-n for a first set), generates a set of write slice requests432 that includes the set of encoded data slices, and sends the set ofwrite slice requests 432 to the set of DST execution units 1-n of theDST execution unit set 1. The set of DST execution units 1-n stores theset of encoded data slices for each received set of encoded data slicesof the portion of the data.

FIG. 42B illustrates further steps of the example of the storing of thedata to produce the stored data. In the example, when the cumulativesize of the received data is greater than the size threshold level, theoutbound DS processing module 80 facilitate storage of remainingportions of the received data 430 in the DST execution unit set 1. Forexample, for each remaining portion, the outbound DS processing module80 partitions the remaining portion into data segments, and for eachdata segment, dispersed storage error encodes the data segment toproduce another set of encoded data slices, issues another set of writeslice requests 432 that includes the other set of encoded data slices tothe set of DST execution units 1-n of the DST execution unit set 2. Theset of DST execution units 1-n of the DST execution unit set 2 storesthe other set of encoded data slices etc. For instance, the set of DSTexecution units 1-n of the DST execution unit set 2 stores encoded dataslices 3-1, 3-2, through 3-n etc.

When the cumulative size of the received data is greater than a sizethreshold level, the outbound DS processing module 80 furtherfacilitates migration of one or more sets of encoded data slices of thereceived data from the DST execution unit set 1 to the DST executionunit set 2. For example, the outbound DS processing module 80 retrievesencoded data slices 1-1, 1-2, through 1-n from the DST execution unitset 1 and stores the retrieved encoded data slices in the DST executionunit set 2 etc. When confirming that the migration has been completed,the outbound DS processing module 80 may facilitate deletion of the oneor more sets of encoded data slices of the received data from the DSTexecution unit set 1. For example, the outbound DS processing module 80issues delete slice requests to the set of DST execution units 1-n ofthe DST execution unit set 1 to delete the one or more sets of encodeddata slices of the received data.

Having migrated the encoded data slices to the DST execution unit set 2,the outbound DS processing module 80 generates metadata of the data thatincludes an association of one or more of a storage location of thereceived data within the DST execution unit set 1, identity of thereceived data, and identity of the sets of encoded data slices.Alternatively, when the cumulative size of all of the received data isnot greater than the size threshold level, the outbound DS processingmodule 80 generates the metadata to indicate that storage of the data isassociated with the DST execution unit set 1.

Having generated the metadata, the outbound DS processing module 80dispersed storage error encodes the metadata to produce a set ofmetadata slices (e.g., M-1, M2, through M-n). The outbound DS processingmodule 80 stores the set of metadata slices in the DST execution unitset 1. For example, the outbound DS processing module 80 issues a set ofwrite slice requests 432 to the set of DST execution units 1-n of theDST execution unit set 1, where the set of write slice requests 432includes the set of metadata slices. The set of DST execution units 1-nof the DST execution unit set 1 stores the set of metadata slices.

Having stored the set of metadata slices, the outbound DS processingmodule 80 associates a storage location (e.g., a source name, a DSNaddress, a set of slice names) of the metadata slices with the identityof the received data. For example, the outbound DS processing module 80updates a DSN directory to associate the identity of the received dataand the source name of the storage location of the set of metadataslices. As another example, the outbound DS processing module 80 updatesan entry of an index node of a dispersed hierarchical index to associatethe identity of the received data and the source name of the storagelocation of the set of metadata slices.

FIG. 42C illustrates an example of the retrieving of the stored data. Asa specific example, the inbound DS processing module 82 identifies thestorage location of the metadata slices based on the identity of thedata for retrieval. For example, the inbound DS processing module 82accesses the DSN directory using the identity of the data for retrievalto recover the source name of the storage location of the metadataslices. Having identified the storage location, the inbound DSprocessing module 82 recovers the metadata using the storage location ofthe metadata slices. For example, the inbound DS processing module 82issues a read threshold number of read slice requests to the set of DSTexecution units 1-n of the DST execution unit set 1 that corresponds tothe storage location, where the read slice requests includes slice namesof the metadata slices, receives read slice responses 434 from the DSTexecution unit set 1, and dispersed storage error decodes a decodethreshold number of extracted metadata slices from the received readslice responses to reproduce the metadata.

Having recovered the metadata, the inbound DS processing module 82identifies a storage location of the data for retrieval from thereproduced metadata. For example, the inbound DS processing module 82extracts a DSN address from the reproduced metadata and determines anidentifier of a corresponding DST execution unit set (e.g., set 2).Having identified the storage location of the data, the inbound DSprocessing module 82 retrieves one or more sets of encoded data slicesusing the storage location. For example, the inbound DS processingmodule 82 issues a set of read slice requests to the DST execution unitset 2, where the set of read slice requests includes one or more sets ofslice names corresponding to the one or more sets of encoded data slicesand receives read slice responses from the set of DST execution units1-n of the DST execution unit set 2. Having received the read sliceresponses 434, the inbound DS processing module 82 disperse storageerror decodes a decode threshold number of encoded data slices of eachof one or more sets of encoded data slices to produce a plurality ofrecovered data segments and aggregates the plurality of recovered datasegments to produce the recovered data 436.

FIG. 42D is a flowchart illustrating another example of accessing data.The accessing of the data includes storing of the data and retrieving ofthe data. As a specific example of the storing of the data, the methodbegins or continues at step 438 where a processing module (e.g., of adistributed storage and task (DST) client module) receives data andwhile a cumulative size of the data being received is less than a sizethreshold level, the processing module stores a portion of the receiveddata in a first set of storage units. For example, the processing modulepartitions a portion of the received data to produce a data segment,dispersed storage error encodes the data segment to produce a set ofencoded data slices, and issues a set of write slice requests to thefirst set of storage units, where the set of write slice requestincludes the set of encoded data slices.

When a cumulative size of the data being received is greater than thesize threshold level, the method continues at step 440 where theprocessing module stores remaining portions of the received data in asecond set of storage units. For example, the processing modulepartitions the remaining portions of the received data to produce datasegments, and for each additional data segment, dispersed storage errorencodes the additional data segment to produce an additional set ofencoded data slices, and issues an additional set of write slicerequests to the second set of storage units, where the additional set ofwrite slice requests includes the additional set of encoded data slices.

When the cumulative size of the data being received is greater than thesize threshold level, the method continues at step 442 where theprocessing module facilitates migration of one or more portions of thereceived data from the first set of storage units to the second set ofstorage units. For example, for each set of encoded data slices storedin the first set of storage units, the processing module retrieves eachof the sets of encoded data slices and stores each of the sets ofencoded data slices of the second set of storage units. The methodcontinues at step 444 where the processing module generates metadata ofthe data that includes an association of a storage location of theportions of the received data in the second set of storage units and theidentity of the data.

The method continues at step 446 where the processing module dispersedstorage error encodes the metadata to produce a set of metadata slices.The method continues at step 448 where the processing module stores theset of metadata slices in the first set of storage units. The methodcontinues at step 450 where the processing module associates theidentity of the data with a storage location of the metadata slices. Forexample, the processing module updates at least one of a dispersedstorage network (DSN) directory and a dispersed hierarchical index.

As a specific example of the retrieving of the data, the methodcontinues or begins at step 452 where the processing module identifiesthe storage location of the set of metadata slices based on identity ofdata for retrieval. For example, the processing module accesses at leastone of the DSN directory in the dispersed hierarchical index using theidentity of the data to recover the storage location. The methodcontinues at step 454 where the processing module recovers the metadatafrom the first set of storage units using the storage location. Forexample, the processing module issues a set of read slice requests tothe first set of storage units using the storage location, receivesmetadata slices, and dispersed storage error decodes a decode thresholdnumber of metadata slices to reproduce the metadata.

The method continues at step 456 where the processing module identifiesa storage location for the data for retrieval from the recoveredmetadata. For example, the processing module extracts a DSN address fromthe recovered metadata and identifies the storage location for the databased on the DSN address (e.g., performs a DSN address to storagelocation lookup to identify the second set of storage units).

The method continues at step 458 where the processing module retrievesat least a decode threshold number of encoded data slices of each set ofencoded data slices of a plurality of sets of encoded data slicescorresponding to the portions of the data from the second set of storageunits using the storage location for the data. For example, theprocessing module generates one or more sets of read slice requestsusing the storage location for the data, sends the one or more sets ofread slice requests to the second set of storage units, receives readslice responses, and extracts a decode threshold number of encoded dataslices from each set of received encoded data slices.

For each set of encoded data slices, the method continues at step 460where the processing module decodes the at least the decode thresholdnumber of encoded data slices to reproduce the data for retrieval. Forexample, the processing module disperse storage error decodes a decodethreshold number of encoded data slices of the at least the decodethreshold number of encoded data slices for each set of encoded dataslices to reproduce a corresponding data segment and aggregates each ofthe corresponding reproduced data segments to reproduce the data forretrieval.

FIG. 43A is a schematic block diagram of an embodiment of a storageservice access system that includes the user device 12 of FIG. 1, thedistributed storage and task (DST) processing unit 16 of FIG. 1, one ormore authentication servers 462, and at least one storage service 464.The storage service 464 includes one or more of a dispersed storagenetwork (DSN), a Web services provider (e.g., Amazon Web Services(AWS)), and a distributed storage and task network (DSTN).

The storage service access system functions to authenticate access tothe storage service 464. In an example of operation, the user device 12(e.g., a requesting entity with regards to the requesting access to thestorage service, alternatively a storage service provider on behalf ofthe user device 12) issues a generate key request 466 to the DSTprocessing unit 16. The generate key request 466 includes one or more ofa user name associated with a user, and a password associated with theusername and user. The DST processing unit 16 identifies one of theauthentication servers 462 based on the generate key request 466 (e.g.,based on the username and a mapping of usernames to authenticationservers).

The DST processing unit 16 issues an authentication request 468 to theidentified authentication server, where the authentication request 468includes the generate key request 466 (e.g., the username and thepassword). The authentication server 462 authenticates theauthentication request 468 by comparing the authentication request 468to authentication records and account status information. When theauthentication server 462 determines that the authentication request 468is favorably authenticated, the authentication server 462 issues anauthentication response 470 to the DST processing unit 16. Theauthentication response 470 includes one or more of the authenticationrequest 468 and an account identifier (ID) associated with the usernameand/or user.

The DST processing unit 16 determines whether the generate key request466 is authenticated based on the authentication response 470. Forexample, the DST processing unit 16 indicates that the generate keyrequest 466 is authenticated when the authentication response 470includes the account ID. Having authenticated the generate key request,the DST processing unit 16 generates a storage key and a storage key ID.The storage key includes a secret key to be associated with the accountID and may be utilized to access the storage service. For example, theDST processing unit 16 generates a random AWS key as the storage key. Asanother example, the DST processing unit 16 generates another storageservice key as the storage key such that the storage key is compatiblewith the storage service 464. The DST processing unit 16 may generateanother random number to produce the storage key ID.

Having generated the storage key and the storage key ID, the DSTprocessing unit 16 generates an index entry of an index (e.g., of adispersed hierarchical index, of a local index) to include one or moreof the storage key, the storage key ID, the account ID, an identifier ofthe identified authentication server (e.g., authentication server ID),where an index key to locate the entry of the index may be based on oneor more of the storage key ID, the authentication server ID, the accountID, and a storage key value. Having generated the index entry of theindex, the DST processing unit 16 updates the index to include thegenerated index entry. For example, the DST processing unit 16 accessesa DSN memory using the index key to search the dispersed hierarchicalindex for an index node, retrieves the index node, updates the indexnode to include the index entry, and stores the updated index node inthe DSN memory to update the dispersed hierarchical index.

Having updated the index, the DST processing unit 16 issues a generatekey response 472 to the user device 12, where the generate key response472 includes the storage key ID and may include the storage key. Havingreceived the generate key response 472, the user device 12 issues anaccess validation request 474 to the DST processing unit 16, where theaccess validation request 474 includes the storage key ID and asignature request. The DST processing unit 16 accesses the index usingthe storage key ID to recover the index entry and extract one or more ofthe storage key, the account ID, and the authentication server ID. TheDST processing unit 16 may issue another authentication request 468 toan authentication server 462 associated with the authentication serverID and receive another authentication response 470.

When the other authentication response 470 is favorable (e.g., theuser/account ID is still authenticated), the DST processing unit 16validates the signature request using the storage key. For example, theDST processing unit 16 signs the signature request using the storagekey. Having validated the signature request, the DST processing unit 16issues an access validation response 476 to the user device 12. Havingreceived the access validation response 476, the user device 12 issues astorage service access request 478 to the storage service 464, where thestorage service access request includes the validated signature request.The storage service 464 processes the storage service access request 478and issues a storage service access response 478 to the user device.Alternatively, or in addition to, the storage service may issue agenerate key request as a query 480 to the DST processing unit 16 andreceive the generate key response on behalf of the user device 12 as aquery response 482.

FIG. 43B is a flowchart illustrating an example of authentication accessto a storage service. The method begins or continues to establishauthentication at step 484 where a processing module (e.g., of adistributed storage and task (DST) client module) receives a generatekey request from a requesting entity (e.g., a storage service on behalfof a user device, the user device) for an accessing entity (e.g., theuser device). The method continues at step 486 where the processingmodule issues an authentication request to a correspondingauthentication module based on the generate key request. For example,the processing module identifies the authentication module based on thegenerate key request, generates the authentication request to include ausername and password of the generate key request, sends theauthentication request to the identified authentication module, andreceives an authentication response.

The method continues at step 488 where the processing module determineswhether the authentication is favorable based on the receivedauthentication response from the authentication module. For example, theprocessing module indicates that the authentication is favorable whenthe received authentication response indicates that the requestingentity and/or the accessing entity are authenticated. When theauthentication is favorable, the method continues at step 490 where theprocessing module generates a storage key for the accessing entity. Forexample, the processing module generates a secret key as the storage keyand an identifier (ID) of the storage key (e.g., storage key ID).

The method continues at step 492 where the processing module generatesan index entry to include access information. The access informationincludes one or more of an account ID of the accessing entity, thestorage key ID, the storage key, an identifier of the authenticationmodule, and at least one indexing key (e.g., the processing module maygenerate the indexing key based on one or more of the storage key ID,the authentication module ID, the account ID, and the storage key). Themethod continues at step 494 where the processing module updates one ormore dispersed hierarchical indexes to include the index entry based onone or more indexing keys. For example, the processing module searches afirst dispersed hierarchical index using a selected indexing key, addsthe index entry to an identified index node, and stores the updatedindex node in the dispersed hierarchical index (e.g., encodes theupdated index node to produce a set of index slices and facilitatestorage of the set of index slices in a dispersed storage network (DSN)memory). The method continues at step 496 where the processing moduleissues a generate key response to the requesting entity, where thegenerate key response includes one or more of the storage key ID and thestorage key.

The method continues where the processing module begins to facilitateaccess to the storage service at step 498 when the processing modulereceives an access validation request from the accessing entity. Theaccess validation request includes one or more of the storage key ID anda signature request. The method continues at step 500 where theprocessing module accesses a corresponding dispersed hierarchical indexbased on the access validation request to recover the index entry. Forexample, the processing module searches the dispersed hierarchical indexusing the storage key ID of the request as an indexing key and extractsone or more of the storage key, the account ID, and the authenticationmodule ID from an identified index entry of the index. Alternatively,the processing module accesses a list of index entries using the accountID to recover the index entry.

The method continues at step 502 where the processing module issues anauthentication request to the corresponding authentication module basedon the recovered index entry. For example, the processing moduleidentifies data from an authentication module from the index entry,generates the authentication request to include the account ID, sendsthe authentication request to the identified a convocation module, andreceives an authentication response.

The method continues at step 504 where the processing module determineswhether the authentication is favorable based on the receivedauthentication response from the authentication module. When theauthentication is favorable, the method continues at step 506 where theprocessing module issues a favorable access validation response to theaccessing entity. For example, the processing module validates thesignature request from the accessing entity to produce a validatedsignature, generates the favorable access validation response to includethe validated signature request, and sends the favorable accessvalidation response to the accessing entity.

The method continues at step 508 where the accessing entity accesses thestorage service using the favorable access validation response. Forexample, the accessing entity generates an access request that includesthe validated signature, sends the access request to the storageservice, and receives an access response from the storage service.

FIGS. 44A-B are schematic block diagrams of another embodiment of adispersed storage network (DSN) illustrating another example of storingdata, where the DSN includes the distributed storage and task (DST)client module 34 of FIG. 1, the network 24 of FIG. 1, and a DSTexecution unit set 510. The DST client module 34 includes the outbounddispersed storage (DS) processing module 80 and the inbound DSprocessing module 82 of FIG. 3. The DST execution unit set 510 includesa set of DST execution units 36 of FIG. 1, where one or more DSTexecution units are deployed at one or more sites. Each DST executionunit provides at least one storage slot of N storage slots. A storageslot includes at least one virtual storage location associated withphysical memory of the DST execution unit. For example, the DSTexecution unit set 510 includes DST execution units 1-14 when 30 storageslots are provided and a varying number of storage slots are associatedwith each DST execution unit. The DSN functions to store data to the setof DST execution unit set 510 and to retrieve the data from the DSTexecution unit set 510.

FIG. 44A illustrates initial steps of an example of operation of thestoring of the data to the DST execution unit set 510, where theoutbound DS processing module 80 receives a write data object request512 from a requesting entity. The write data object request 512 includesone or more of a data object for storage in the DSN, a data identifier(ID) of the data, an ID of the requesting entity, and a desiredperformance level indicator. Having received the write data objectrequest 512, the outbound DS processing module 80 obtains dispersalparameters. The dispersal parameters includes one or more of a number ofstorage slots N, an information dispersal algorithm (IDA) width number,a write threshold number, a read threshold number, and a decodethreshold number. The obtaining includes at least one of retrieving aportion of system registry information, utilizing a predetermination,determining based on the desired performance level indicator, andaccessing a list based on the requesting entity ID.

Having obtained the dispersal parameters, the outbound DS processingmodule 80 selects a set of primary storage slots of N storage slotsassociated with the DST execution unit set, where the set of storageslots includes at least a decode threshold number of storage slots andat most an IDA width number of storage slots. The selecting may be basedon one or more of DST execution unit availability information, a DSTexecution unit performance level, site availability information, systemtopology information, a system loading level, a system loading goallevel, a data storage availability goal, a data retrieval reliabilitygoal, and a site selection scheme. As a specific example, the outboundDS processing module 80 selects the IDA width number of storage slotsout of the N storage slots. As such, the outbound DS processing module80 selects one permutation out of a number of permutations expressed bya formula: number of permutations of the selecting of the IDA widthnumber of storage slots=N choose IDA width. For instance, the number ofpermutations of selecting the IDA width number of storage slots=30choose 15=155 million permutations, when N=30 and the IDA width=15.

Storage of data within the DST execution unit set can tolerate a numberof storage slot failures and/or unavailability without affecting datastorage availability and data retrieval reliability in accordance with aformula: number of storage slot failures tolerated=N−IDA width=30-15=15.As such, the storage of data within the DST execution unit set cantolerate 15 storage slot failures.

The outbound DS processing module 80 may select the IDA width number ofstorage slots in accordance with the site selection scheme to improvethe data retrieval reliability. For example, the outbound DS processingmodule 80 selects storage slots at each site of the one or more sitessuch that at least a decode threshold number of encoded data slices areavailable from available storage slots at a minimum desired number ofsites. As a specific example, the outbound DS processing module 80selects storage slots associated with available and better-than-averageperforming DST execution units such that the decode threshold number ofencoded data slices are available from any two operational sites whenone of three total sites is unavailable. For instance, the outbound DSprocessing module 80 selects 5 storage slots at each of the 3 sites whenthe IDA width is 15 and the decode threshold is 10.

Having selected the set of primary storage slots, the outbound DSprocessing module 80 encodes the data object using a dispersed storageerror encoding function and in accordance with the dispersal parametersto produce a plurality of sets of encoded data slices. For example, theoutbound DS processing module 80 encodes a first data segment of aplurality of data segments of the data object to produce a first set ofencoded data slices, where the first set of encoded data slices includesthe IDA width number of slices and the first data segment may berecovered when at least any decode threshold number of encoded dataslices of the set of encoded data slices is retrievable.

Having encoded the data object, the outbound DS processing module 80,identifies DST execution units associated with the selected set ofprimary storage slots. The identifying may be based on one or more of atable lookup (e.g., a storage slot to DST execution unit mapping),initiating a query, and receiving a query response. For example, theoutbound DS processing module 80 identifies DST execution units 1, 2, 3,5, 6, 8, 10, 12, and 13 based on accessing the storage slot to DSTexecution unit mapping.

Having identified the DST execution units associated with the selectedset of primary storage slots, the outbound DS processing module 80identifies an underperforming DST execution unit (e.g., poorperformance, failing, failed) of the identified DST execution unitsassociated with the selected set of primary storage slots. Theidentifying may be based on one or more of receiving an error message,performing a test, interpreting test results, and monitoring performanceinformation associated with the identified DST execution units. Forexample, the outbound DS processing module 80 identifies DST executionunit 13 as the underperforming DST execution unit based on receiving anerror message from DST execution unit 13, where the error message isinterpreted to indicate underperformance.

Having identified underperforming DST execution unit, the outbound DSprocessing module 80 identifies one or more primary storage slotsassociated with the underperforming DST execution unit. For example, theprocessing module accesses the storage slot to DST execution unitmapping to identify the one or more primary storage slots associatedwith the underperforming DST execution unit. For instance, the outboundDS processing module 80 identifies primary storage slot 29 associatedwith DST execution unit 13 by accessing the storage slot to DSTexecution unit mapping.

For each of the one or more identified primary storage slots associatedwith the underperforming DST execution unit, the outbound DS processingmodule 80 replicates an associated encoded data slice of each of theplurality sets of encoded data slices to produce replicated encoded dataslices. For example, the outbound DS processing module 80 identifiesencoded data slice 15 associated with primary storage slot 29 andreplicates encoded data slice 15 of each of the sets of encoded dataslices to produce replicated encoded data slices 15.

Having produced the replicated encoded data slices, the outbound DSprocessing module 80 generates one or more sets of write slice requests514, where the one or more sets of write slice requests 514 includes theplurality of sets of encoded data slices and the replicated encoded dataslices. Having generated the one or more sets of write slice requests514, the outbound DS processing module 80, for each replicated slice,selects an alternate storage slot associated with another DST executionunit, where the other DST execution unit is not underperforming. Theselecting may be based on one or more of the slice to storage slotmapping, performance levels of the DST execution units, a DST executionunit performance threshold level, a performance goal, a network loadinglevel, and a network loading level goal. For example, the outbound DSprocessing module 80 selects storage slot 30 associated with DSTexecution unit 14 for storage of the replicated encoded data slices 15when performance levels of the DST execution unit 14 is greater than theDST execution unit performance threshold level (e.g., notunderperforming).

Having selected the alternate storage slot, the outbound DS processingmodule 80 sends, via the network 24, the one or more sets of write slicerequests 514 to the identified DST execution units and to the other DSTexecution unit. As an example of the sending the one or more sets ofwrite slice requests to the identified DST execution units, the outboundDS processing module 80 sends, via the network 24, write slice requests514 to store encoded data slices 1-2 in storage slots 1-2 of DSTexecution unit 1, encoded data slices 3-4 in storage slots 4-5 of DSTexecution unit 2, encoded data slice 5 in storage slot 7 of DSTexecution unit 3, encoded data slice 6 in storage slot 13 of DSTexecution unit 5, encoded data slices 7-9 in storage slots 14-16 of DSTexecution unit 6, encoded data slice 10 in storage slot 19 of DSTexecution unit 8, encoded data slices 11-12 in storage slots 23-24 ofDST execution unit 10, encoded data slices 13-14 in storage slots 27-28of DST execution unit 12, and encoded data slice 15 in storage slot 29of underperforming DST execution unit 13. As an example of the sendingof the one or more sets of write slice requests 514 to the other DSTexecution unit, the outbound DS processing module 80 sends, via thenetwork 24, at least one write slice request 514 to store replicatedencoded data slices 15 in storage slot 30 of DST execution unit 14.

Having sent the one or more sets of write slice requests 514, theoutbound DS processing module 80 receives, via the network 24, writeslice responses 516 from at least some DST execution units of the DSTexecution unit set. Each write slice response 516 includes a writeoperation status indicator. The write operation status indicatorincludes a favorable indication when a corresponding write slice requestwas successfully executed. The write operation status indicator includesan unfavorable indication when the corresponding write slice request wasnot successfully executed (e.g., due to an error). The example ofoperation continues as is discussed in greater detail with reference toFIG. 44B.

FIG. 44B illustrates further steps of the example of operation of thestoring of the data to the DST execution unit set, where the outbound DSprocessing module 80, for each replicated encoded data slice, selectsone storage slot of the storage slot associated with the encoded dataslice and the alternate storage slot associated with the replicatedencoded data slice based on one or more of the received write sliceresponses, a performance level, a performance level goal, and apredetermination. For example, the outbound DS processing module 80selects the alternate storage slot when receiving a favorable writeslice response from DST execution unit 14 with regards to the storage ofthe replicated encoded data slice 15 in storage slot 30 of the DSTexecution unit 14 and not receiving a write slice response from DSTexecution unit 13 with regards to the storage of the encoded data slice15 in storage slot 29 within a storage time frame. As another example,the outbound DS processing module 80 selects the storage slot whenreceiving a favorable write slice response from DST execution unit 13.

Having selected the one storage slot, the outbound DS processing module80 issues a commit request 518, via the network 24, to a DST executionunit associated with the selected one storage slot. For example, theoutbound DS processing module 80 generates and sends, via the network24, the commit request 518 to DST execution unit 14 when the oneselected storage slot is storage slot 30 associated with DST executionunit 14, where the commit request 518 indicates to commit redundantencoded data slice 15.

Having sent the commit request 518, the outbound DS processing module 80issues, for a remaining storage slot of the storage slot associated withthe encoded data slice and the alternate storage slot associated withthe replicated encoded data slice, a rollback request 520. For example,the outbound DS processing module 80 generates and sends, via thenetwork 24, the rollback request to DST execution unit 13 where therollback request 520 indicates to rollback storage of the encoded dataslice 15.

Having issued the rollback request 520, the outbound DS processingmodule 80, for each other encoded data slice of each set of encoded dataslices (e.g., non-replicated slices), issues, via the network 24, acommit request 518 to an associated DST execution unit in accordancewith one or more of a corresponding received write slice response andthe slice to storage slot mapping. As a specific example, the outboundDS processing module 80 generates and sends, via the network 24, commitrequests 518 to commit storage of encoded data slices 1-2 in storageslots 1-2 of DST execution unit 1, encoded data slices 3-4 in storageslots 4-5 of DST execution unit 2, encoded data slice 5 in storage slot7 of DST execution unit 3, encoded data slice 6 in storage slot 13 ofDST execution unit 5, encoded data slices 7-9 in storage slots 14-16 ofDST execution unit 6, encoded data slice 10 in storage slot 19 of DSTexecution unit 8, encoded data slices 11-12 in storage slots 23-24 ofDST execution unit 10, and encoded data slices 13-14 in storage slots27-28 of DST execution unit 12.

FIG. 44C is a flowchart illustrating an example of storing data. Themethod begins or continues at step 522 where a processing module (e.g.,of a distributed storage and task (DST) client module) selects a set ofprimary storage slots from N storage slots associated with a set ofstorage units. The method continues at step 524 where the processingmodule encodes data for storage in accordance with dispersal parametersto produce a plurality of sets of encoded data slices. The methodcontinues at step 526 where the processing module identifies anunderperforming storage unit associated with a primary storage slot ofthe selected set of primary storage slots. For example, the processingmodule obtains historical storage unit performance information andidentifies a most underperforming storage unit of the set of storageunits.

The method continues at step 528 where the processing module replicateseach encoded data slice associated with the primary storage slot of theunderperforming storage unit to produce replicated encoded data slices.For each replicated encoded data slice, the method continues at step 530where the processing module selects an alternate storage slot associatedwith another storage unit of the set of storage units. For example, theprocessing module interprets the historical performance storage unitperformance information to identify a favorably performing storage unitthat is different than the identified underperforming storage unit.

The method continues at step 532 of the processing module generates oneor more sets of write slice requests, where the one or more sets ofwrite slice requests includes the plurality of sets of encoded dataslices and the replicated encoded data slices. The generating includesgenerating one or more sets of slice names and replicating at least someof the slice names that are associated with the replicated encoded dataslices. The method continues at step 534 where the processing modulesends the one or more sets of write slice requests to the set of storageunits and to the other storage unit. For example, the processing modulesends the one or more sets of write slice requests to storage unitsassociated with the primary set of storage units and at least one writeslice request to the other storage unit. The method continues at step536 where the processing module receives write slice responses from atleast some of the storage units.

For each replicated encoded data slice, the method continues at step 538where the processing module selects one storage slot of the primarystorage slot and the alternate storage slot based on the received writeslice responses. For example, the processing module selects the storageslot when receiving a corresponding favorable write slice response forthe storage slot. As another example, the processing module selects thealternate storage slot when receiving a corresponding favorable writeslice response for the alternate storage slot and not receiving afavorable write slice response corresponding to the storage slot withina response timeframe.

The method continues at step 540 where the processing module issues acommit request to a storage unit associated with the selected onestorage slot. For example, the processing module issues the commitrequest to include a transaction number associated with a correspondingwrite slice request, identifies the storage unit associated with theselected one storage slot, and outputs the commit requests to theidentified storage unit. The method continues at step 542 where theprocessing module issues a rollback request to an un-selected storageunit associated with a remaining storage slot of the storage slot of theprimary storage slots and the alternate storage slot. The issuingincludes generating the rollback request to include the transactionnumber. For each other encoded data slice of each set of encoded dataslices, the method continues at step 544 where the processing moduleissues a commit request to an associated storage unit in accordance witha corresponding received write slice response.

FIGS. 45A-B are schematic block diagrams of another embodiment of adispersed storage network (DSN) illustrating an example of rebuildingstored data. The DSN includes a distributed storage and task (DST)execution unit set 546, the network 24 of FIG. 1, and the DST clientmodule 34 of FIG. 1. The DST execution unit set 546 includes a set ofDST execution units 1-8. Each DST execution unit may be implementedutilizing the DST execution unit 36 of FIG. 1. The DST client module 34includes the inbound dispersed storage (DS) processing module 82 of FIG.3, and the outbound DS processing module 80 of FIG. 3. The DSN functionsto store data as stored data, retrieve stored data to reproduce thedata, and to rebuild stored data. The rebuilding the stored dataincludes rebuilding the stored data while retrieving the stored data.

FIG. 45A illustrates initial steps of an example of the rebuilding ofthe stored data while retrieving the stored data. As a specific example,the inbound DS processing module 82 receives a read data request 548 toretrieve the stored data, where the data is dispersed error encoded toproduce a plurality of sets of encoded data slices that are stored in aset of storage resources (e.g., the set of DST execution units 1-8).Each set of encoded data slices includes an information dispersalalgorithm (IDA) width number of encoded data slices. For example, theIDA width is 8 when producing eight encoded data slices for each set ofencoded data slice. The data can be recovered when at least a decodethreshold number of encoded data slices for each set of encoded dataslices is available. For example, the data may be recovered when 5-8encoded data slices for each set of encoded data slices are availableand the decode threshold number is 5.

Having received the read data request 548, the inbound DS processingmodule 82 generates a read threshold number of read slice requests 550for a read threshold number of encoded data slices of each set ofencoded data slices. The read threshold number is greater than or equalto the decode threshold number and less than or equal to the IDA widthnumber. For example, the inbound DS processing module 82 generates 6read slice requests corresponding to encoded data slices 1-1, 1-2, 1-3,1-4, 1-5, and 1-6 when the read threshold number is 6. Having generatedthe read threshold number of read slice requests 550, the inbound DSprocessing module 82 generates a list slice request 552 for eachremaining encoded data slice of a set of encoded data slices. Forexample, the inbound DS processing module 82 generates a list slicerequest 552 for encoded data slice 1-7 and another list slice request552 for encoded data slice 1-8.

Having generated the read slice requests 550 and the list slice requests552, the inbound DS processing module 82 sends the read threshold numberof read slice requests 550 and the remaining list slice requests 552 tothe set of DST execution units 1-8 corresponding to the set of storageresources (e.g., including in accordance with a mapping of storageresources to DST execution units). For example, the inbound DSprocessing module 82 sends read slice requests 1-6 to DST executionunits 1-6 and sends the list slice requests 7-8 to DST execution units7-8.

Having sent the requests, the inbound DS processing module 82 receivesread slice responses 554 and list slice responses 556 from at least someof the DST execution units. For example, the inbound DS processingmodule 82 receives read slice responses 1-6 from DST execution units 1-7and list slice responses 7-8 from DST execution units 7-8. For each setof encoded data slices, the inbound DS processing module 82 dispersedstorage error decodes a decode threshold number of encoded data slicesof received encoded data slices from the read slice responses 554 toreproduce a data segment of a plurality of data segments. The inbound DSprocessing module 82 aggregates the plurality of data segments toproduce recovered data 549.

For each set of encoded data slices, the inbound DS processing module 82determines whether a slice error has occurred based on the received readslice responses 554 and received list slice responses 556. A slice errorincludes at least one of a missing slice and a corrupted slice. Forexample, the inbound DS processing module 82 indicates that encoded dataslice 1-4 is associated with a slice error when the read slice response4 indicates that the encoded data slice 1-4 is corrupted or missing. Asanother example, the inbound DS processing module 82 indicates thatencoded data slice 1-8 is associated with another slice error when theinbound DS processing module 82 interprets the list slice response 8 anddetects that encoded data slice 1-8 is missing. When the slice error hasoccurred, the inbound DS processing module 82 identifies a correspondingreproduced data segment 558 of the plurality of reproduced datasegments.

FIG. 45B illustrates further steps of the example of the rebuilding ofthe stored data while retrieving the stored data. As a specific example,when the slice error(s) has occurred, the outbound DS processing module80 dispersed storage error encodes the identified reproduced datasegment associated with the slice error(s) to reproduce a correspondingset of encoded data slices. For each slice error, the outbound DSprocessing module 80 generates a write slice request 560 that includes acorresponding reproduced encoded data slice of the reproduced set ofencoded data slices. Having generated the write slice request 560, theoutbound DS processing module 80 selects a storage resource for storingthe corresponding reproduced encoded data slice. The selecting may bebased on one or more of DST execution unit availability, DST executionunit performance, network performance, a predetermination, and a DSTexecution unit solicitation as a store storage unit. For example, theoutbound DS processing module 80 selects DST execution unit 4 forstorage of reproduced encoded data slice 1-4 and selects DST executionunit 8 for storage of reproduced encoded data slice 1-8 when DSTexecution units 4 and 8 are associated with favorable performancelevels.

Having selected the storage resource, the outbound DS processing module80 sends the write slice request 560 to a DST execution unitcorresponding to the selected storage resource. For example, theoutbound DS processing module 80 sends a write slice request 4 to DSTexecution unit 4 for storage of reproduced encoded data slice 1-4 withinthe DST execution unit 4 and sends a write slice request 8 to DSTexecution unit 8 for storage of reproduced encoded data slice 1-8 withinthe DST execution unit 8. Alternatively, the outbound DS processingmodule 80 sends write slice request 8 to DST execution unit 7 when DSTexecution unit 8 is associated with unfavorable performance levels, DSTexecution unit 7 is associated with favorable performance levels, andDST execution unit 7 as indicated availability as a foster storage unit.

FIG. 45C is a flowchart illustrating an example of rebuilding storeddata. The method begins or continues at step 562 where a processingmodule (e.g., of a distributed storage and task (DST) client module)receives a read data request for data stored in a dispersed storagenetwork (DSN) as a plurality of sets of encoded data slices. For eachset of encoded data slices, the method continues at step 564 of theprocessing module retrieves at least a decode threshold number ofencoded data slices from the DSN. For example, the processing moduleissues a read threshold number of read slice requests to a readthreshold number of storage units of a set of storage units of the DSNand receives at least a decode threshold number of favorable read sliceresponses from the read threshold number of storage units.

For each at least a decode threshold number of encoded data slices, themethod continues at step 566 where the processing module determineswhether the remaining encoded data slices of the set of encoded dataslices are favorably stored in the DSN. For example, the processingmodule issues list slice requests to storage units associated with theremaining encoded data slices, receives list slice responses, andindicates that the remaining encoded data slices are favorably storedwhen a sufficient number of encoded data slices are listed by the listslice responses.

For each set of encoded data slices, the method continues at step 568where the processing module decodes a decode threshold number of encodeddata slices of the at least a decode threshold number of encoded dataslices to reproduce a corresponding data segment. For example, theprocessing module selects the decode threshold number of encoded dataslices and dispersed storage error decodes the decode threshold numberof encoded data slices to produce the reproduce corresponding datasegment. Alternatively, or in addition to, the processing moduleaggregates a plurality of reproduced data segments to reproduce the datafor outputting to a requesting entity.

For each set of encoded data slices, the method continues at step 570where the processing module determines whether a storage error hasoccurred. For example, the processing module interprets read sliceresponses and list slice responses to identify a missing and/orcorrupted encoded data slices of one or more storage errors. When thestorage error has occurred, the method continues at step 572 where theprocessing module dispersed storage error encodes a correspondingreproduced data segment to produce a reproduced set of encoded dataslices.

For each storage error, the method continues at step 574 where theprocessing module generates a write slice request that includes acorresponding reproduced encoded data slice. For each write slicerequest, the method continues at step 576 where the processing moduleselects a storage resource for storing the corresponding reproducedencoded data slice. The selecting may be based on one or more of storageresource performance, storage resource availability, and apredetermination. For example, the processing module selects a samestorage resource associated with the storage error when a storage unitassociated with the storage error has favorable storage performance. Asanother example, the processing module selects a foster storage resourcefor temporary storage of the encoded data slice when the storageresource associated with the storage error has an unfavorable attributeand the foster storage resource has favorable performance. The methodcontinues at step 578 where the processing module sends the write slicerequests to the selected storage resource of the DSN.

FIGS. 46A-B are schematic block diagrams of another embodiment of adispersed storage network (DSN) illustrating another example of storingdata. The DSN includes the DST execution unit set 510 of FIG. 44A, thenetwork 24 of FIG. 1, and the DST client module 34 of FIG. 1. The DSTclient module 34 includes the outbound dispersed storage (DS) processingmodule 80 of FIG. 3 and the inbound DS processing module 82 of FIG. 3.The DSN functions to store data to the set of DST execution unit set andto retrieve the data from the DST execution unit set.

FIG. 46A illustrates initial steps of an example of operation of thestoring of the data to the DST execution unit set, where the outbound DSprocessing module 80 receives a write data object request 512 from arequesting entity. The write data object request 512 includes one ormore of a data object for storage in the DSN, a data identifier (ID) ofthe data, an ID of the requesting entity, and a desired performancelevel indicator. Having received the write data object request 512, theoutbound DS processing module 80 obtains dispersal parameters. Thedispersal parameters includes one or more of a number of storage slotsN, an information dispersal algorithm (IDA) width number, a writethreshold number, a read threshold number, and a decode thresholdnumber. The obtaining includes at least one of retrieving a portion ofsystem registry information, utilizing a predetermination, determiningbased on the desired performance level indicator, and accessing a listbased on the requesting entity ID.

Having obtained the dispersal parameters, the outbound DS processingmodule 80 selects a set of primary storage slots of N storage slotsassociated with the DST execution unit set, where the set of storageslots includes at least a decode threshold number of storage slots andat most an IDA width number of storage slots. The selecting may be basedon one or more of DST execution unit availability information, a DSTexecution unit performance level, site availability information, systemtopology information, a system loading level, a system loading goallevel, a data storage availability goal, a data retrieval reliabilitygoal, and a site selection scheme. As a specific example, the outboundDS processing module 80 selects the IDA width number of storage slotsout of the N storage slots. As such, the outbound DS processing module80 selects one permutation out of a number of permutations expressed bya formula: number of permutations of the selecting of the IDA widthnumber of storage slots=N choose IDA width. For instance, the number ofpermutations of selecting the IDA width number of storage slots=30choose 15=155 million permutations, when N=30 and the IDA width=15.

Storage of data within the DST execution unit set can tolerate a numberof storage slot failures and/or unavailability without affecting datastorage availability and data retrieval reliability in accordance with aformula: number of storage slot failures tolerated=N−IDA width=30-15=15.As such, the storage of data within the DST execution unit set cantolerate 15 storage slot failures.

The outbound DS processing module 80 may select the IDA width number ofstorage slots in accordance with the site selection scheme to improvethe data retrieval reliability. For example, the outbound DS processingmodule 80 selects storage slots at each site of the one or more sitessuch that at least a decode threshold number of encoded data slices areavailable from available storage slots at a minimum desired number ofsites. As a specific example, the outbound DS processing module 80selects storage slots associated with available and better-than-averageperforming DST execution units such that the decode threshold number ofencoded data slices are available from any two operational sites whenone of three total sites is unavailable. For instance, the outbound DSprocessing module 80 selects 5 storage slots at each of the 3 sites whenthe IDA width is 15 and the decode threshold is 10.

Having selected the set of primary storage slots, the outbound DSprocessing module 80 encodes the data object using a dispersed storageerror encoding function and in accordance with the dispersal parametersto produce a plurality of sets of encoded data slices. For example, theoutbound DS processing module 80 encodes a first data segment of aplurality of data segments of the data object to produce a first set ofencoded data slices, where the first set of encoded data slices includesthe IDA width number of slices and the first data segment may berecovered when at least any decode threshold number of encoded dataslices of the set of encoded data slices is retrievable.

Having encoded the data object, the outbound DS processing module 80,identifies DST execution units associated with the selected set ofprimary storage slots. The identifying may be based on one or more of atable lookup (e.g., a storage slot to DST execution unit mapping),initiating a query, and receiving a query response. For example, theoutbound DS processing module 80 identifies DST execution units 1, 2, 3,5, 6, 8, 10, 12, and 13 based on accessing the storage slot to DSTexecution unit mapping.

Having identified the DST execution units associated with the selectedset of primary storage slots, the outbound DS processing module 80generates one or more sets of write slice requests 514, where the one ormore sets of write slice requests 514 includes the plurality of sets ofencoded data slices. Having generated the one or more sets of writeslice requests 514, the outbound DS processing module 80 sends, via thenetwork 24, the one or more sets of write slice requests 514 to theidentified DST execution units. For example, the outbound DS processingmodule 80 sends, via the network 24, write slice requests 514 to storeencoded data slices 1-2 in storage slots 1-2 of DST execution unit 1,encoded data slices 3-4 in storage slots 4-5 of DST execution unit 2,encoded data slice 5 in storage slot 7 of DST execution unit 3, encodeddata slice 6 in storage slot 13 of DST execution unit 5, encoded dataslices 7-9 in storage slots 14-16 of DST execution unit 6, encoded dataslice 10 in storage slot 19 of DST execution unit 8, encoded data slices11-12 in storage slots 23-24 of DST execution unit 10, encoded dataslices 13-14 in storage slots 27-28 of DST execution unit 12, andencoded data slice 15 in storage slot 29 of DST execution unit 13.

Having sent the one or more sets of write slice requests 514, theoutbound DS processing module 80 receives, via the network 24, writeslice responses 516 from at least some DST execution units of the DSTexecution unit set. Each read slice response 516 includes a writeoperation status indicator. The write operation status indicatorincludes a favorable indication when a corresponding write slice requestwas successfully executed. The write operation status indicator includesan unfavorable indication when the corresponding write slice request wasnot successfully executed (e.g., due to an error).

Having received the write slice responses 516, the outbound DSprocessing module 80 identifies one or more write failures based on thereceived write slice responses 516. For example, the outbound DSprocessing module 80 identifies write failures associated with storageof encoded data slices 13-14 in storage slots 27-28 of DST executionunit 12 when a corresponding write slice response has not been receivedfrom DST execution unit 12 within a response timeframe (e.g., DSTexecution unit 12 is unavailable). The example of operation continues asis discussed in greater detail with reference to FIG. 46B.

FIG. 46B illustrates further steps of the example of operation of thestoring of the data to the DST execution unit set, where the outbound DSprocessing module 80, for each write failure, generates a foster encodeddata slice. For example, the outbound DS processing module 80 generatesa foster encoded data slice 13 for encoded data slice 13 and a fosterencoded data slice 14 for encoded data slice 14. Having generated thefoster encoded data slices, the outbound DS processing module 80 obtainscapacity information for the DST execution unit set. For example, theoutbound DS processing module 80 issues capacity information requests580 to the DST execution unit set and receives capacity informationresponses 582. The capacity information may include one or more of totalcapacity, capacity utilized, available capacity, and capacityutilization growth rate.

For each foster encoded data slice, the outbound DS processing module 80selects a storage slot based on the obtained capacity information forthe DST execution unit set. The selecting includes selecting how manyfoster encoded data slices to store in each storage slot in accordancewith a selection scheme. The selection scheme includes rank orderingstarting with most available capacity, selecting at least one storageunit for all slices, and selecting a different storage unit for eachfoster encoded data slice. For example, the outbound DS processingmodule 80 selects storage slot 25 of DST execution unit 11 for storageof foster encoded data slice 14 and selects storage slot 30 of DSTexecution unit 14 for storage of foster encoded data slice 13 when DSTexecution unit 14 has a most available storage space of storage unitssupporting secondary slots followed by DST execution unit 11 etc.

For each foster encoded data slice, the outbound DS processing module 80issues a write slice request 514 to a DST execution units thatcorresponds to the selected storage slots for the foster encoded dataslice. The write slice request 514 includes the foster encoded dataslice. For example, the outbound DS processing module 80 issues a writeslice request 514 to DST execution unit 11 that includes foster encodeddata slice 14 and issues another write slice request to DST executionunit 14 that includes foster encoded data slice 13.

FIG. 46C is a flowchart illustrating another example of storing data,which include similar steps to FIG. 44C. The method begins or continueswith steps 524 and 522 of FIG. 44C where a processing module (e.g., of adistributed storage and task (DST) client module) encodes data forstorage in accordance with dispersal parameters to produce a pluralityof sets of encoded data slices and selects a set of primary storageslots from N storage slots associated with a set of storage units.

The method continues at step 584 where the processing module identifiesstorage units of the set of storage units associated with the selectedset of primary storage slots. For example, the processing moduleperforms a lookup based on the selected primary storage slots toidentify the storage units. The method continues at step 586 where theprocessing module generates one or more sets of write slice requests toinclude the plurality of sets of encoded data slices. The methodcontinues at step 588 where the processing module sends the one or moresets of write slice requests to the identified storage units. The methodcontinues with step 536 of FIG. 44C where the processing module receiveswrite slice responses.

The method continues at step 590 where the processing module determineswhether one or more write failures have occurred based on the receivedwrite slice responses. When the one or more write failures haveoccurred, for each write failure, the method continues at step 592 wherethe processing module generates a foster encoded data slice. Forexample, the processing module indicates a write failure when notreceiving a write slice response within a response timeframe. The methodcontinues at step 594 where the processing module obtains capacityinformation for at least some storage units of the set of storage units.

For each foster encoded data slice, the method continues at step 596where the processing module selects a storage slot based on the capacityinformation. For example, the processing module selects the storage slotbased on the capacity information in accordance with a by rank orderingselection scheme. For each foster encoded data slice, the methodcontinues at step 598 where the processing module issues a write slicerequest to a storage unit that corresponds to the selected storage slotsfor the foster encoded data slice. For example, the processing modulegenerates the write slice requests to include the foster encoded dataslice and sends the write slice request to the storage unit.

FIG. 47A is a schematic block diagram of another embodiment of adispersed storage network (DSN) that includes at least two distributedstorage and task (DST) client modules 1-2, the network 24 of FIG. 1, anda DST execution unit set 600. Each DST client module may be implementedusing the DST client module 34 of FIG. 1. Each DST client moduleincludes the outbound DS processing module 80 of FIG. 3. The DSNfunctions to resolve write conflicts while storing data in the DSTexecution unit set.

In an example of operation of the resolving of the write conflicts, DSTexecution unit 1 dispersed storage error encodes data A-1 to produce aplurality of sets of encoded data slices 1 (e.g., each set includesencoded data slices 1, 2, 3, through n), generates a set of write slicerequests range 1 that includes the plurality of sets of encoded dataslices 1, and sends, via the network 24, the set of write slice requestsrange 1 to the set of DST execution units 1-n. The range 1 includes arange of slice names associated with the plurality of sets of encodeddata slices from data A-1. For example, the DST client module 1 sends,via the network 24, range 1 encoded data slices 1 to DST execution unit1, range 1 encoded data slices 2 to DST execution unit 2, etc.

Substantially simultaneously, DST execution unit 2 dispersed storageerror encodes data A-2 to produce a plurality of sets of encoded dataslices 2 (e.g., each set includes encoded data slices 1, 2, 3, throughn), generates a set of write slice requests range 2 that includes theplurality of sets of encoded data slices 2, and sends, via the network24, the set of write slice requests range 2 to the set of DST executionunits 1-n. The range 2 includes another range of slice names associatedwith the plurality of sets of encoded data slices from data A-2. Forexample, the DST client module 2 sends, via the network 24, range 2encoded data slices 2 to DST execution unit 1, range 2 encoded dataslices 2 to DST execution unit 2, etc.

Each DST execution unit of the DST execution unit set 600 receives acorresponding write slice request from one of the DST client module 1and the DST client module 2, where the write slice request includes aplurality of encoded data slices for storage in the DST execution unitand a corresponding plurality of slice names of the plurality of encodeddata slices. Having received the write slice request, the DST executionunit interprets the plurality of slice names to produce a slice namerange (e.g., a high and low slice name produces the range). Havingproduced the slice name range, the DST execution unit determines whethera write lock conflict exists based on the slice name range. For example,the processing module indicates the write lock conflict when the slicename range conflicts with a previously and still active locked slicename range of the DST execution unit.

When the write lock conflict does not exist, the DST execution unitindicates that the slice name ranges now locked, initiates local storageof the received plurality of encoded data slices, issues a favorablewrite slice response to the corresponding one of the DST client modules1 and 2, and indicates that the slice name range is not locked whencompleting the local storage of the plurality of encoded data slices(e.g., completing after receiving a corresponding commit transactionrequest).

When the write lock conflict does exist, the DST execution unit issuesan unfavorable write slice response to the corresponding one of the DSTclient modules 1 and 2. The unfavorable write slice response indicatesthat the write lock conflict exists.

FIG. 47B is a flowchart illustrating an example of resolving writeconflicts. The method begins or continues at step 602 where a processingmodule (e.g., of a distributed storage and task (DST) execution unit, ofa storage unit) receives a write slice request from a requesting entity,where the write slice request includes a plurality of encoded dataslices and the corresponding plurality of slice names. The methodcontinues at step 604 where the processing module interprets theplurality of slice names to produce a slice name range. The interpretingincludes identifying a lowest slice name and a high slice name of thecorresponding plurality of slice names to produce the slice name range.

The method continues at step 606 where the processing module determineswhether a write lock conflict exists based on the slice name range. Forexample, the processing module indicates that the write lock conflictexists when the slice name range conflicts with a lock slice name range.For instance, the slice name range overlaps with a retrieved lockedslice name range of a currently active write lock. When the writeconflict exists, the method continues at step 608 where the processingmodule issues an unfavorable write slice response to the requestingentity. For example, the processing module generates the unfavorablewrite slice response to indicate that the write lock conflict exists,and sends the write slice response to the requesting entity. When thewrite lock conflict does not exist, the method branches to step 610.

The method continues at step 610 where the processing module indicatesthat the slice name range is locked when the write conflict does notexist. For example, the processing module updates a lock slice name listto include the slice name range. The method continues at step 612 wherethe processing module initiates local storage of the plurality ofencoded data slices. For example, the processing module stores theplurality of encoded data slices in the memory of the storage unit.

The method continues at step 614 where the processing module issues afavorable write slice response to the requesting entity. For example,the processing module generates the favorable write slice response toindicate a favorable write slice operation and sends the favorable writeslice response to the requesting entity. The issuing may further includereceiving at least one of a rollback transaction request and a committransaction request followed by at least one of a finalize transactionrequest or an undo transaction request.

The method continues at step 616 where the processing module indicatesthat the slice name range is not locked when completing the localstorage of the plurality of encoded data slice. For example, theprocessing module receives the finalize transaction request and updatesthe locked slice name list to indicate that the slice name range is notlocked.

FIG. 48A is a schematic block diagram of another embodiment of adispersed storage network (DSN) that includes the distribute storage andtask (DST) client module 34 of FIG. 1, the network 24 of FIG. 1, and theDST execution unit set 600 of FIG. 47A. The DST execution unit setincludes a set of DST execution units 1-n. The DST client module 34includes the outbound dispersed storage (DS) processing module 80 ofFIG. 3 and the inbound DS processing module 82 of FIG. 3. The outboundDS processing module 80 includes a selection module 618, a compressionmodule 620, and the DS error encoding 112 of FIG. 4. The inbound DSprocessing module 80 includes the DS error decoding 182 of FIG. 13, ade-compression module 622, and a de-selection module 624. The DSNfunctions to store and retrieve a plurality of correlated data.

In an example of operation of the storing the plurality of correlateddata, the outbound DS processing module 80 receives a plurality ofsorted data entries 626, where the sorted data entries share a commonaffiliation. The common affiliation includes at least one of belongingto a common index node of a dispersed hierarchical index, being sortedwith similar sorting factor outcomes, sharing a common data type,sharing a common data source, sharing a common data owner, belonging toa common storage vault, etc. The receiving of the plurality of sorteddata entries may include searching the dispersed hierarchical index andrecovering the common index node that includes the sorted data entries.

Having obtained the plurality of sorted data entries 626, the outboundDS processing module 80 obtains a data access goal level associated withthe plurality of sorted data entries. The obtaining includes at leastone of performing a lookup, determining based on historical performance,and receiving. Such data access goal levels include a data accesslatency goal, a data access bandwidth goal, and a data access transferrate goal.

Having obtained the data access goal level, the outbound DS processingmodule 80 obtains a DSN performance information. The DSN performanceinformation includes one or more of access latency, bandwidth, transferrates, resource availability levels, local memory capacity, availableprocessing capacity levels, and available storage levels. The obtainingincludes at least one of performing a lookup, accessing a historicalrecord, initiating a query, receiving a query response, initiating atest, and interpreting a test result.

Having obtained the DSN performance information, the outbound DSprocessing module 80 selects compression parameters based on one or moreof the data access goal level and the DSN performance information. Forexample, the outbound DS processing module 80 performs an iterativefunction to estimate data access performance based on a given set ofcompression parameters and the DSN performance information, compares theestimated data access performance to the data access goal level andadjusts the compression parameters such that the estimated performanceis substantially the same as the data access goal level. The compressionparameters include one or more of a compression algorithm identifier, acompression level, an allocated memory level, a desired size ofcompressed data, and a size of the data object for compression. Dataaccess latency includes a number of access cycles multiplied by a sum ofan individual access latency and the individual compression relatedlatency.

Having selected the compression parameters, the selection module selectssorted data entries to produce a data object 628 based on the selectedcompression parameters. For example, a data object A includes aplurality of index keys 1, 2, 3, 4, etc., and corresponding content 1,2, 3, 4, etc. Having produced the data object 628, the compressionmodule compresses the data object 628 to produce a compressed dataobject 630 in accordance with the selected compression parameters. Forexample, the compression module compresses a data object A using theselected compression parameters to produce a compressed data object A.

Having produced the compressed data object 630, the DS error encoding112 dispersed storage error encodes the compressed data object toproduce one or more sets of encoded data slices. The outbound DSprocessing module 80 issues, via the network 24, write slice requests634 to the set of DST execution units 1-n, where the write slicerequests 634 includes encoded data slices 1-n of each set of encodeddata slices. The outbound DS processing module 80 receives write sliceresponses 636 from the DST execution unit set indicating whether the oneor more sets of encoded data slices have been successfully stored.

In an example of operation of the retrieving of the plurality ofcorrelated data, the inbound DS processing module 82 issues read slicerequests 638 to the set of DST execution units 1-n and receives readslice responses 640 from at least some of the set of DST execution units1-n, where the read slice responses 640 includes encoded data slices ofthe one or more sets of encoded data slices. Having received the readslice responses, the DS error decoding 182, for each set of encoded dataslices, decodes a decode threshold number of received encoded dataslices to reproduce the compressed data object 630. The de-compressionmodule 622 decompresses the compressed data object 630 to reproduce thedata object 628. The de-selection module 624 selects one or more entriesof the reproduced data object to provide recovered sorted data entries632.

FIG. 48B is a flowchart illustrating an example of storing a pluralityof correlated data. The method begins or continues at step 642 where aprocessing module (e.g., of a distributed storage and task (DST) clientmodule) obtains a plurality of sorted data entries. For example, theprocessing module searches a dispersed hierarchical index of a dispersedstorage network (DSN) to recover an index node that includes acompressed data object that includes plurality of sorted data entriesand decompresses the compressed data object to produce the sorted dataentries. The method continues at step 644 where the processing moduleobtains a data access performance goal level associated with theplurality of sorted data entries. For example, the processing moduleaccesses system registry information and interprets historicalperformance information to produce the data access performance goallevel.

The method continues at step 646 where the processing module obtains DSNperformance information. The obtaining includes one or more of accessinghistorical DSN performance information, initiating a performance test,and interpreting a performance test result. The method continues at step648 where the processing module selects compression parameters based onthe data access performance goal level and the DSN performanceinformation. For example, the processing module performs an iterativefunction that includes estimating a performance based on a set ofcompression parameters and adjusting the compression parameters toprovide estimated performance that is substantially the same as the dataaccess performance level.

The method continues at step 650 where the processing module selectssorted data entries of the plurality of sorted data entries based on theselected compression parameters to produce a data object. The selectingincludes one or more of utilizing a number of entries from thecompression parameters, selecting all entries from a previous recoveryoperation of an index node, selecting a first sorted subset, selecting alast sorted subset, and selecting a middle sorted subset. The processingmodule may initiate generating of another data object to store remainingsorted data entries.

The method continues at step 652 where the processing module compressesthe data object to produce a compressed data object using the selectedcompression parameters. For example, the processing module applies acompression algorithm of the compression parameters to the data objectto produce the compressed data object. the method continues at step 654where the processing module disperse storage error encodes thecompressed data object to produce one or more sets of encoded dataslices for storage in a set of storage units. For example, theprocessing module encodes the compressed data object to produce one ormore sets of encoded data slices, issues one or more sets of write slicerequests that includes the one or more sets of encoded data slices tothe set of storage units. When the other data object is generated, theprocessing module may encode the other data object to produce more setsof encoded data slices for storage in the set of storage units.

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “operably coupled to”, “coupled to”, and/or “coupling” includesdirect coupling between items and/or indirect coupling between items viaan intervening item (e.g., an item includes, but is not limited to, acomponent, an element, a circuit, and/or a module) where, for indirectcoupling, the intervening item does not modify the information of asignal but may adjust its current level, voltage level, and/or powerlevel. As may further be used herein, inferred coupling (i.e., where oneelement is coupled to another element by inference) includes direct andindirect coupling between two items in the same manner as “coupled to”.As may even further be used herein, the term “operable to” or “operablycoupled to” indicates that an item includes one or more of powerconnections, input(s), output(s), etc., to perform, when activated, oneor more its corresponding functions and may further include inferredcoupling to one or more other items. As may still further be usedherein, the term “associated with”, includes direct and/or indirectcoupling of separate items and/or one item being embedded within anotheritem. As may be used herein, the term “compares favorably”, indicatesthat a comparison between two or more items, signals, etc., provides adesired relationship. For example, when the desired relationship is thatsignal 1 has a greater magnitude than signal 2, a favorable comparisonmay be achieved when the magnitude of signal 1 is greater than that ofsignal 2 or when the magnitude of signal 2 is less than that of signal1.

As may also be used herein, the terms “processing module”, “processingcircuit”, and/or “processing unit” may be a single processing device ora plurality of processing devices. Such a processing device may be amicroprocessor, micro-controller, digital signal processor,microcomputer, central processing unit, field programmable gate array,programmable logic device, state machine, logic circuitry, analogcircuitry, digital circuitry, and/or any device that manipulates signals(analog and/or digital) based on hard coding of the circuitry and/oroperational instructions. The processing module, module, processingcircuit, and/or processing unit may be, or further include, memoryand/or an integrated memory element, which may be a single memorydevice, a plurality of memory devices, and/or embedded circuitry ofanother processing module, module, processing circuit, and/or processingunit. Such a memory device may be a read-only memory, random accessmemory, volatile memory, non-volatile memory, static memory, dynamicmemory, flash memory, cache memory, and/or any device that storesdigital information. Note that if the processing module, module,processing circuit, and/or processing unit includes more than oneprocessing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the Figures. Such a memorydevice or memory element can be included in an article of manufacture.

The present invention has been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claimed invention. Further, theboundaries of these functional building blocks have been arbitrarilydefined for convenience of description. Alternate boundaries could bedefined as long as the certain significant functions are appropriatelyperformed. Similarly, flow diagram blocks may also have been arbitrarilydefined herein to illustrate certain significant functionality. To theextent used, the flow diagram block boundaries and sequence could havebeen defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claimed invention. One of average skill in the artwill also recognize that the functional building blocks, and otherillustrative blocks, modules and components herein, can be implementedas illustrated or by discrete components, application specificintegrated circuits, processors executing appropriate software and thelike or any combination thereof.

The present invention may have also been described, at least in part, interms of one or more embodiments. An embodiment of the present inventionis used herein to illustrate the present invention, an aspect thereof, afeature thereof, a concept thereof, and/or an example thereof. Aphysical embodiment of an apparatus, an article of manufacture, amachine, and/or of a process that embodies the present invention mayinclude one or more of the aspects, features, concepts, examples, etc.,described with reference to one or more of the embodiments discussedherein. Further, from figure to figure, the embodiments may incorporatethe same or similarly named functions, steps, modules, etc., that mayuse the same or different reference numbers and, as such, the functions,steps, modules, etc., may be the same or similar functions, steps,modules, etc., or different ones.

While the transistors in the above described figure(s) is/are shown asfield effect transistors (FETs), as one of ordinary skill in the artwill appreciate, the transistors may be implemented using any type oftransistor structure including, but not limited to, bipolar, metal oxidesemiconductor field effect transistors (MOSFET), N-well transistors,P-well transistors, enhancement mode, depletion mode, and zero voltagethreshold (VT) transistors.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of the various embodimentsof the present invention. A module includes a processing module, afunctional block, hardware, and/or software stored on memory forperforming one or more functions as may be described herein. Note that,if the module is implemented via hardware, the hardware may operateindependently and/or in conjunction software and/or firmware. As usedherein, a module may contain one or more sub-modules, each of which maybe one or more modules.

While particular combinations of various functions and features of thepresent invention have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent invention is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method for execution in a storage network (SN),the method comprises: identifying a data object of a plurality of dataobjects for retrieval from the SN, wherein the plurality of data objectsis combined to produce a concatenated data object and wherein theconcatenated data object is encoded in accordance with a dispersedencoding function to produce a set of encoded data blocks; identifyingan encoded data block of the set of encoded data blocks corresponding tothe data object based on a mapping of the plurality of data objects;retrieving the encoded data block from a storage unit; and decoding theencoded data block in accordance with the dispersed encoding functionand the mapping to reproduce the data object.
 2. The method of claim 1,wherein the concatenated data object is encoded by: generating aplurality of data blocks; and dispersed error encoding the plurality ofdata blocks to produce the set of encoded data blocks.
 3. The method ofclaim 2, wherein the data object is mapped to the encoded data block ofthe plurality of data blocks.
 4. The method of claim 1, wherein thedispersed encoding function includes a Cauchy-Reed-Solomon encoding or aReed-Solomon encoding.
 5. The method of claim 1, wherein the dispersedencoding function includes a forward error-correction encoding.
 6. Themethod of claim 1, wherein the mapping of the plurality of data objectsincludes a mapping of the plurality of data objects to a data structurecorresponding to a plurality of data blocks, wherein the data object ismapped to one or more of the plurality of data blocks.
 7. The method ofclaim 6, wherein the data structure is a data matrix that includes theplurality of data blocks.
 8. A computer readable memory comprises: amemory section that stores operational instructions that, when executedby a computing device of a storage network (SN), causes the computingdevice to perform operations that include: identifying a data object ofa plurality of data objects for retrieval from the SN, wherein theplurality of data objects is combined to produce a concatenated dataobject and wherein the concatenated data object is encoded in accordancewith a dispersed encoding function to produce a set of encoded datablocks; identifying an encoded data block of the set of encoded datablocks corresponding to the data object based on a mapping of theplurality of data objects; retrieving the encoded data block from astorage unit; and decoding the encoded data block in accordance with thedispersed encoding function and the mapping to reproduce the dataobject.
 9. The computer readable memory of claim 8, wherein theconcatenated data object is encoded by: generating a plurality of datablocks; and dispersed error encoding the plurality of data blocks toproduce the set of encoded data blocks.
 10. The computer readable memoryof claim 9, wherein the data object is mapped to the encoded data blockof the plurality of data blocks.
 11. The computer readable memory ofclaim 8, wherein the dispersed encoding function includes aCauchy-Reed-Solomon encoding or a Reed-Solomon encoding.
 12. Thecomputer readable memory of claim 8, wherein the dispersed encodingfunction includes a forward error-correction encoding.
 13. The computerreadable memory of claim 8, wherein the mapping of the plurality of dataobjects includes a mapping of the plurality of data objects to a datastructure corresponding to a plurality of data blocks, wherein the dataobject is mapped to one or more of the plurality of data blocks.
 14. Thecomputer readable memory of claim 13, wherein the data structure is adata matrix that includes the plurality of data blocks.
 15. A device ofa storage network (SN), the device comprises: an interface; a localmemory; and a processing module operably coupled to the interface andthe local memory, wherein the processing module functions to performoperations that include: identifying a data object of a plurality ofdata objects for retrieval from the SN, wherein the plurality of dataobjects is combined to produce a concatenated data object and whereinthe concatenated data object is encoded in accordance with a dispersedencoding function to produce a set of encoded data blocks; identifyingan encoded data block of the set of encoded data blocks corresponding tothe data object based on a mapping of the plurality of data objects;retrieving the encoded data block from a storage unit; and decoding theencoded data block in accordance with the dispersed encoding functionand the mapping to reproduce the data object.
 16. The device of claim15, wherein the concatenated data object is encoded by: generating aplurality of data blocks; and dispersed error encoding the plurality ofdata blocks to produce the set of encoded data blocks.
 17. The device ofclaim 16, wherein the data object is mapped to the encoded data block ofthe plurality of data blocks.
 18. The device of claim 15, wherein thedispersed encoding function includes a forward error-correctionencoding.
 19. The device of claim 15, wherein the dispersed encodingfunction includes a Cauchy-Reed-Solomon encoding or a Reed-Solomonencoding.
 20. The device of claim 15, wherein the mapping of theplurality of data objects includes a mapping of the plurality of dataobjects to a data structure corresponding to a plurality of data blocks,wherein the data object is mapped to one or more of the plurality ofdata blocks.